Search

Current statistical models to simulate pandemics miss the most relevant information about the close atomic interactions between individuals which is the key aspect of virus spread. Thus, they lack a proper visualization of such interactions and their impact on virus spread. In the field of computer graphics, and more specifically in computer animation, there have been many crowd simulation models to populate virtual environments. However, the focus has typically been to simulate reasonable paths between random or semi-random locations in a map, without any possibility of analyzing specific individual behavior. We propose a crowd simulation framework to accurately simulate the interactions in a city environment at the individual level, with the purpose of recording and analyzing the spread of human diseases. By simulating the whereabouts of agents throughout the day by mimicking the actual activities of a population in their daily routines, we can accurately predict the location and duration of interactions between individuals, thus having a model that can reproduce the spread of the virus due to human-to-human contact. Our results show the potential of our framework to closely simulate the virus spread based on real agent-to-agent contacts. We believe that this could become a powerful tool for policymakers to make informed decisions in future pandemics and to better communicate the impact of such decisions to the general public., This work has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska Curie grant agreement No 860768 (CLIPE project). Also, it was partially funded by grants PID2021-122136OB- C21 and PID2021-122136OB-C22 funded by MCIN/AEI/https://doi.org/10.13039/ 50110 0011033 and by ERDF A way of making Europe., Peer Reviewed, Postprint (published version)

Human and animal presence in natural landscapes is initially revealed by the immediate impact of their locomotion, from footprints to crushed grass. In this work, we present an approach to model the effects of virtual characters on natural terrains, focusing on the impact of human locomotion. We introduce a lightweight solution to compute accurate foot placement on uneven ground and infer dynamic foot pressure from kinematic animation data and the mass of the character. A ground and vegetation model enables us to effectively simulate the local impact of locomotion on soft soils and plants over time, resulting in the formation of visible paths. As our results show, we can parameterize various soil materials and vegetation types validated with real-world data. Our method can be used to significantly increase the realism of populated natural landscapes and the sense of presence in virtual applications and games., This work is part of the project SENDA (TED2021-129761B-I00), funded by MCIN/AEI/10.13039/501100011033 and the European Union “NextGenerationEU”/PRTR. It is also part of the European Union’s Horizon 2020 research and innovation programme CLIPE, under the Marie Skłodowska-Curie grant agreement No. 860768., Peer Reviewed, Postprint (published version)

In this paper, we discuss the requirements and technical challenges within the EHEM project, Enhancement of Heritage Experiences: The Middle Ages, an ongoing research program for the acquisition, analysis, documentation, interpretation, digital restoration, and communication of medieval artistic heritage. The project involves multidisciplinary teams comprising art historians and visual computing experts. Despite the vast literature on digital 3D models in support of Cultural Heritage, the field is so rich and diverse that specific projects often imply distinct, unique requirements which often challenge the computational technologies and suggest new research opportunities. As good representatives of such diversity, we describe the three monuments that serve as test cases for the project, all of them with a rich history of architecture and paintings. We discuss the art historians’ view of how digital models can support their research, the expertise and technological solutions adopted so far, as well as the technical challenges in multiple areas spanning geometry and appearance acquisition, color analysis and digital restitution, as well as the representation of the profound transformations due to the alterations suffered over the centuries., The EHEM project was approved in the JPI Cultural Heritage Conservation, Protection, and Use (0127) call in 2020. The JPICH has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 699523. This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation, and Digital Policy. This work has been partially funded from MCIN/AEI/10.13039/501100011033/FEDER, UE (Spain) in the framework of the project PID2021-122136OB-C21, and with the support of the Department of Research and Universities of the Government of Catalonia (2021 SGR 01035)., Peer Reviewed, Postprint (published version)

An increasing number of virtual reality applications require environments that emulate real-world conditions. These environments often involve dynamic virtual humans showing realistic behaviors. Understanding user perception and navigation among these virtual agents is key for designing realistic and effective environments featuring groups of virtual humans. While collision risk significantly influences human locomotion in the real world, this risk is largely absent in virtual settings. This paper studies the impact of the expected collision feedback on user perception and interaction with virtual crowds. We examine the effectiveness of commonly used collision feedback techniques (auditory cues and tactile vibrations) as well as inducing participants to expect that a physical bump with a real person might occur, as if some virtual humans actually correspond to real persons embodied into them and sharing the same physical space. Our results indicate that the expected collision feedback significantly influences both participant behavior—encompassing global navigation and local movements—and subjective perceptions of presence and copresence. Specifically, the introduction of a perceived risk of actual collision was found to significantly impact global navigation strategies and increase the sense of presence. Auditory cues had a similar effect on global navigation and additionally enhanced the sense of copresence. In contrast, vibrotactile feedback was primarily effective in influencing local movements., This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860768 (CLIPE project), and from MCIN/AEI/10.13039/501100011033/FEDER, UE (PID2021- 122136OB-C21), ”A way to make Europe”. Jose Luis Ponton was also funded by the Spanish Ministry of Universities (FPU21/01927)., Peer Reviewed, Postprint (author's final draft)

© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Generative models have received a lot of attention in many areas of academia and the industry. Their capabilities span many areas, from the invention of images given a prompt to the generation of concrete code to solve a certain programming issue. These two paradigmatic cases fall within two distinct categories of requirements, ranging from "creativity" to "precision", as characterized by Bing Chat, which employs ChatGPT-4 as its backbone. Visualization practitioners and researchers have wondered to what end one of such systems could accomplish our work in a more efficient way. Several works in the literature have utilized them for the creation of visualizations. And some tools such as Lida, incorporate them as part of their pipeline. Nevertheless, to the authors’ knowledge, no systematic approach for testing their capabilities has been published, which includes both extensive and in-depth evaluation. Our goal is to fill that gap with a systematic approach that analyzes three elements: whether Large Language Models are capable of correctly generating a large variety of charts, what libraries they can deal with effectively, and how far we can go to configure individual charts. To achieve this objective, we initially selected a diverse set of charts, which are commonly utilized in data visualization. We then developed a set of generic prompts that could be used to generate them, and analyzed the performance of different LLMs and libraries. The results include both the set of prompts and the data sources, as well as an analysis of the performance with different configurations., Supported by Ministerio de Ciencia e Innovación/AEI (PID2021-122136OB-C21 by 10.13039/501100011033/FEDER, UE)., Peer Reviewed, Postprint (author's final draft)

Signed distance fields (SDFs) have emerged as an alternative shape representation for real-time collision detection and lighting effects. Computing these for complex models can be expensive, so one popular approach is to prepare an approximation via sampling and interpolation. Then, these may be rendered using sphere marching, which gets close to the surface quickly, but needs several iterations to converge to it. In this paper, we propose an alternative that computes the intersection of a given ray and the surface analytically at a narrow band. This may be combined with other enhancements like having variable error for the approximation depending on the distance to the surface and skipping regions that do not contain the surface to accelerate the outer band ray traversal while reducing the required memory. To achieve smoother representations with minimal computational cost, we propose a method for computing surface intersections and normals from separate interpolants. We evaluate all these to find the optimal combination improving the rendering performance and memory consumption of these SDF approximations., This work has been partially funded by Ministeri de Ciència i Innovació(MICIN), Agencia Estatal de Investigación (AEI) and the Fons Europeu de Desenvolupament Regional (FEDER) (project PID2021-122136OB-C21 funded by MCIN/AEI/10.13039/501100011033/ FEDER, UE); and by the Department of Research and Universities of the Government of Catalonia (2021 SGR 01035). The first author gratefully acknowledges the Universitat Politècnica de Catalunya and Banco Santander for the financial support of his predoctoral grant FPI UPC grant., Peer Reviewed, Postprint (published version)

Recent advances in computer vision and deep learning techniques have opened new possibilities regarding the automatic labeling of sport videos. However, an essen-tial requirement for supervised techniques is the availability of accurately labeled training datasets. In this paper we present PadelVic, an annotated dataset of an ama-teur padel match which consists of multi-view video streams, estimated positional data for all four players within the court (and for one of the players, accurate motion capture data of his body pose), as well as synthetic videos specifically designed to serve as training sets for neural networks estimating positional data from videos. For the recorded data, player positions were estimated by applying a state-of-the-art pose estimation technique to one of the videos, which yields a relatively small positional error (M=16 cm, SD=13 cm). For one of the players, we used a motion capture system providing the orientation of the body parts with an accuracy of 1.5º RMS. The highest accuracy though comes from our synthetic dataset, which provides ground-truth po-sitional and pose data of virtual players animated with the motion capture data. As an example application of the synthetic dataset, we present a system for a more accurate prediction of the center-of-mass of the players projected onto the court plane, from a single-view video of the match. We also discuss how to exploit per-frame positional data of the players for tasks such as synergy analysis, collective tactical analysis, and player profile generation., This work has received funding from project PID2021-122136OB-C21 funded by MCIN/AEI and FEDER “A way to make Europe”. Mohammadreza Javadiha and Jose Luis Ponton were also funded by the Spanish Ministry of Science, Innovation and Universities, grants PRE2018-086835 and FPU21/01927., Peer Reviewed, Postprint (published version)

Weathering effects caused by physical, chemical, or biological processes result in visible damages that alter the appearance of stones’ surfaces. Consequently, weathered stone monuments can offer a distorted perception of the artworks to the point of making their interpretation misleading. Being able to detect and monitor decay is crucial for restorers and curators to perform important tasks such as identifying missing parts, assessing the preservation state, or evaluating curating strategies. Decay mapping, the process of identifying weathered zones of artworks, is essential for preservation and research projects. This is usually carried out by marking the affected parts of the monument on a 2D drawing or picture of it. One of the main problems of this methodology is that it is manual work based only on experts’ observations. This makes the process slow and often results in disparities between the mappings of the same monument made by different experts. In this paper, we focus on the weathering effect known as “scaling”, following the ICOMOS ISCS definition. We present a novel technique for detecting, segmenting, and classifying these effects on stone monuments. Our method is user-friendly, requiring minimal user input. By analyzing 3D reconstructed data considering geometry and appearance, the method identifies scaling features and segments weathered regions, classifying them by scaling subtype. It shows improvements over previous approaches and is well-received by experts, representing a significant step towards objective stone decay mapping., This work has been partially supported by projects PID2021-122136OB-C21 and PID2021-122136OB-C22 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe and developed in the context of Grup de Recerca Consolidat ViRVIG 2021-SGR-01035 with the support of the Departament of Research and Universities of the Generalitat de Catalunya., Peer Reviewed, Postprint (author's final draft)

The creation of truly believable simulated natural environments remains an unsolved problem in Computer Graphics. This is, in part, due to a lack of visual variety. In nature, apart from variation due to abiotic and biotic growth factors, a significant role is played by disturbance events, such as fires, windstorms, disease, and death and decay processes, which give rise to both standing dead trees (snags) and downed woody debris (logs). For instance, snags constitute on average 10% of unmanaged forests by basal area, and logs account for 2 1/2 times this quantity. While previous systems have incorporated individual elements of disturbance (e.g., forest fires) and decay (e.g., the formation of humus), there has been no unifying treatment, perhaps because of the challenge of matching simulation results with generated geometric models. In this paper, we present a framework that combines an ecosystem simulation, which explicitly incorporates disturbance events and decay processes, with a model realization process, which balances the uniqueness arising from life history with the need for instancing due to memory constraints. We tested our hypothesis concerning the visual impact of disturbance and decay with a two-alternative forced-choice experiment (n = 116). Our findings are that the presence of dead wood in various forms, as snags or logs, significantly improves the believability of natural scenes, while, surprisingly, general variation in the number of model instances, with up to 8 models per species, and a focus on disturbance events, does not., This work was funded by the project AMPLI ANR-20-CE23-0001, supported by Agence Nationale de la Recherche (France), by the National Research Foundation of South Africa (Grant Number: 129257) and is also part of a Maria Zambrano fellowship by Ministerio de Universidades (Spain)., Peer Reviewed, Postprint (author's final draft)

VR United is a virtual reality application that we have developed to support multiple people simultaneously interacting in the same environment. Each person is represented with a virtual body that looks like themselves. Such immersive shared environments have existed and been the subject of research for the past 30 years. Here, we demonstrate how VR United meets criteria for successful interaction, where a journalist from the Financial Times in London interviewed a professor in New York for two hours. The virtual location of the interview was a restaurant, in line with the series of interviews published as “Lunch with the FT.” We show how the interview was successful, as a substitute for a physically present one. The article based on the interview was published in the Financial Times as normal for the series. We finally consider the future development of such systems, including some implications for immersive journalism., VR United was developed under the European Research Council project “Moments in Time in Immersive Virtual Environments” (MoTIVE) (#742989). The particular application for the interview was funded under the Horizon 2020 programme H2020-FETPROACT-2020-2 (#101017884) GuestXR., Peer Reviewed, Postprint (author's final draft)

The segmentation of medical models is a complex and time-intensive process required for both diagnosis and surgical preparation. Despite the advancements in deep learning, neural networks can only automatically segment a limited number of structures, often requiring further validation by a domain expert. In numerous instances, manual segmentation is still necessary. Virtual Reality (VR) technology can enhance the segmentation process by providing improved perception of segmentation outcomes and enabling interactive supervision by experts. But inspecting how the progress of the segmentation algorithm is evolving, and defining new seeds requires seeing the inner layers of the volume, which can be costly and difficult to achieve with typical metaphors such as clipping planes. In this paper, we introduce a wedge-shaped 3D interaction metaphor designed to facilitate VR-based segmentation through detailed inspection and guidance. User evaluations demonstrated increased satisfaction with usability and faster task completion times using the tool., Research funded by PID2021-122136OB-C21 from the Ministerio de Ciencia e Innovación, Spain, by 839 FEDER (EU) funds., Peer Reviewed, Postprint (published version)

Heatmaps are a widely used technique in visualization. Unfortunately, they have not been investigated in depth and little is known about the best parameterizations so that they are properly interpreted. The effect of different palettes on our ability to read values is still unknown. To address this issue, we conducted a user study, in which we analyzed the effect of two commonly used color palettes, Blues and Viridis, on value estimation and value search. As a result, we provide some suggestions for what to expect from the heatmap configurations analyzed., This paper has been supported by PID2021-122136OB-C21 from the Ministerio de Ciencia e Innovación, by 839 FEDER (EU) funds. Elena Molina has been supported by FI-SDUR doctoral grant from Generalitat de Catalunya, and FPU grant from the Ministerio de Ciencia e Innovación., Peer Reviewed, Postprint (published version)

Recent advances in sensor technologies, in particular video-based human detection, object tracking and pose estimation, have opened new possibilities for the automatic or semi-automatic per-frame annotation of sport videos. In the case of racket sports such as tennis and padel, state-of- the-art deep learning methods allow the robust detection and tracking of the players from a single video, which can be combined with ball tracking and shot recognition techniques to obtain a precise description of the play state at every frame. These data, which might include the court-space position of the players, their speeds, accelerations, shots and ball trajectories, can be exported in tabular format for further analysis. Unfortunately, the limitations of traditional table-based methods for analyzing such sport data are twofold. On the one hand, these methods cannot represent complex spatio-temporal queries in a compact, readable way, usable by sport analysts. On the other hand, traditional data visualization tools often fail to convey all the information available in the video (such as the precise body motion before, during and after the execution of a shot) and resulting plots only show a small portion of the available data. In this paper we address these two limitations by focusing on the analysis of video-based tracking data of padel matches. In particular, we propose a domain-specific query language to facilitate coaches and sport analysts to write queries in a very compact form. Additionally, we enrich the data visualization plots by linking each data item to a specific segment of the video so that analysts have full access to all the details related to the query. We demonstrate the flexibility of our system by collecting and converting into readable queries multiple tips and hypotheses on padel strategies extracted from the literature., Postprint (published version)

Environmental noise pollution is a problem for cities’ inhabitants, that can be especially severe in large cities. To implement measures that can alleviate this problem, it is necessary to understand the extent and impact of different noise sources. Although gathering data is relatively cheap, processing and analyzing the data is still complex. Besides the lack of an automatic method for labelling city sounds, maybe more important is the fact that there is not a tool that allows domain experts to analytically explore data that has been manually labelled. To solve this problem, we have created a visual analytics application that facilitates the exploration of multiple-labelled temporal data captured at four different corners of a crossing in a populated area of Barcelona, the Eixample neighborhood. Our tool consists of a series of linked interactive views that facilitate top-down (from noise events to labels) and bottom-up (from labels to time slots) exploration of the captured data., This project has been supported by grants TIN2017-88515-C2-1-R (GEN3DLIVE) from the Spanish Ministerio de Economía y Competitividad, by 839 FEDER (EU) funds, and PID2021-122136OB-C21 from MCIN/AEI/10.13039/501100011033/FEDER, EU., Peer Reviewed, Postprint (published version)

Digital color restitution aims to digitally restore the original colors of a painting. Existing image editing applications can be used for this purpose, but they require a select-and-edit workflow and thus they do not scale well to large collections of paintings or different regions of the same painting. To address this issue, we propose an automated workflow that requires only a few representative source colors and associated target colors as input from art historians. The system then creates a control grid to model a deformation of the CIELAB color space. Such deformation can be applied to arbitrary images of the same painting. The proposed approach is suitable for restituting the color of images from a large photographic campaign, as well as for the textures of 3D reconstructions of a monument. We demonstrate the benefits of our method on a collection of mural paintings from a medieval monument., This work has been partially supported by projects PID2021-122136OB-C21 and PID2021-122136OB-C22 funded by MCIN/AEI/ 10.13039/501100011033 and by ERDF A way of making Europe, by the EU Horizon 2020, JPICH Conservation, Protection and Use initiative (JPICH-0127) and the Spanish Agencia Estatal de Investigación (grant PCI2020-111979)., Peer Reviewed, Postprint (published version)

The use of self-avatars is gaining popularity thanks to affordable VR headsets. Unfortunately, mainstream VR devices often use a small number of trackers and provide low-accuracy animations. Previous studies have shown that the Sense of Embodiment, and in particular the Sense of Agency, depends on the extent to which the avatar's movements mimic the user's movements. However, few works study such effect for tasks requiring a precise interaction with the environment, i.e., tasks that require accurate manipulation, precise foot stepping, or correct body poses. In these cases, users are likely to notice inconsistencies between their self-avatars and their actual pose. In this paper, we study the impact of the animation fidelity of the user avatar on a variety of tasks that focus on arm movement, leg movement and body posture. We compare three different animation techniques: two of them using Inverse Kinematics to reconstruct the pose from sparse input (6 trackers), and a third one using a professional motion capture system with 17 inertial sensors. We evaluate these animation techniques both quantitatively (completion time, unintentional collisions, pose accuracy) and qualitatively (Sense of Embodiment). Our results show that the animation quality affects the Sense of Embodiment. Inertial-based MoCap performs significantly better in mimicking body poses. Surprisingly, IK-based solutions using fewer sensors outperformed MoCap in tasks requiring accurate positioning, which we attribute to the higher latency and the positional drift that causes errors at the end-effectors, which are more noticeable in contact areas such as the feet., This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 860768 (CLIPE project) and from MCIN/AEI/10.13039/501100011033/FEDER, UE (PID2021-122136OB-C21). Jose Luis Ponton was also funded by the Spanish Ministry of Universities (FPU21/01927)., Peer Reviewed, Postprint (author's final draft)

User studies are a useful tool for researchers, allowing them to collect data on how users perceive, interact with and process different types of sensory information. If planned in advance, user experiments can be leveraged in every stage of a research project, from early design, prototyping and feature exploration to applied proofs of concept, passing through validation and data collection for model training. User studies can provide the researcher with different types of information depending on the chosen methodology: user performance metrics, surveys and interviews, field studies, physiological data, etc. Considering human perception and other cognitive processes is particularly important in computer graphics, where most research produces outputs whose ultimate purpose is to be seen or perceived by a human. Being able to measure in an objective and systematic way how the information we generate is integrated into the representational space humans create to situate themselves in the world means that researchers will have more information to implement optimal algorithms, tools and techniques. In this tutorial we will give an overview of good practices for user studies in computer graphics with a particular focus on virtual reality use cases. We will cover the basics on how to design, carry out and analyze good user studies, as well as different particularities to be taken into account in immersive environments., Peer Reviewed, Postprint (published version)

Background: Persecutory delusions are a major psychiatric problem that often do not respond sufficiently to standard pharmacological or psychological treatments. We developed a new brief automated virtual reality (VR) cognitive treatment that has the potential to be used easily in clinical services. We aimed to compare VR cognitive therapy with an alternative VR therapy (mental relaxation), with an emphasis on understanding potential mechanisms of action. Methods: THRIVE was a parallel-group, single-blind, randomised controlled trial across four UK National Health Service trusts in England. Participants were included if they were aged 16 years or older, had a persistent (at least 3 months) persecutory delusion held with at least 50% conviction, reported feeling threatened when outside with other people, and had a primary diagnosis from the referring clinical team of a non-affective psychotic disorder. We randomly assigned (1:1) patients to either THRIVE VR cognitive therapy or VR mental relaxation, using a permuted blocks algorithm with randomly varying block size, stratified by severity of delusion. Usual care continued for all participants. Each VR therapy was provided in four sessions over approximately 4 weeks, supported by an assistant psychologist or clinical psychologist. Trial assessors were masked to group allocation. Outcomes were assessed at 0, 2 (therapy mid-point), 4 (primary endpoint, end of treatment), 8, 16, and 24 weeks. The primary outcome was persecutory delusion conviction, assessed by the Psychotic Symptoms Rating Scale (PSYRATS; rated 0–100%). Outcome analyses were done in the intention-to-treat population. We assessed the treatment credibility and expectancy of the interventions and the two mechanisms (defence behaviours and safety beliefs) that the cognitive intervention was designed to target. This trial is prospectively registered with the ISRCTN registry, ISRCTN12497310. Findings: From Sept 21, 2018, to May 13, 2021 (with a pause due to CO, The trial was funded by the Medical Research Council Developmental Pathway Funding Scheme (MR/P02629X/1). It was also supported by the National Institute for Health and Care Research (NIHR) Oxford Health Biomedical Research Centre (BRC-1215-2000). DF is an NIHR Senior Investigator. DMC is an Emeritus NIHR Senior Investigator. This paper presents independent research funded by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. FW is funded by a Wellcome Trust Clinical Doctoral Fellowship (102176/B/13/Z). MS is supported by the European Research Council Grant MoTIVE (742989)., Peer Reviewed, Article signat per 23 autors/es: Department of Experimental Psychology (Prof D Freeman DClinPsy, R Lister DClinPsy, F Waite DClinPsych, S Lambe DClinPsy, A Beckley MA, E Bold BSc, L Jenner BA, R Diamond DClinPsych, M Kirkham DClinPsych, E Twivy DClinPsych, C Causier MSc, L Carr BSc, S Saidel MSc, A Rovira PhD, Prof D M Clark DPhil, L Rosebrock PhD), Oxford Primary Care Clinical Trials Unit, Nuffield Department of Primary Care Health Sciences (U Galal MSc, L-M Yu PhD), University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK (Prof D Freeman, F Waite, S Lambe, R Diamond, A Rovira, Prof D M Clark, L Rosebrock); Black Country Healthcare NHS Foundation Trust, Dudley, UK (R Lister); Northamptonshire Healthcare NHS Foundation Trust, Kettering, UK (R Day BSc, A Ivins DClinPsych, R Nah DClinPsy); Event Lab, Faculty of Psychology Spain (A Beacco PhD, Prof M Slater DSc), Institute of Neurosciences (Prof M Slater), University of Barcelona, Barcelona, Spain; Universitat Politècnica de Catalunya, Barcelona, Spain (A Beacco); Central and North West London NHS Foundation Trust, London, UK (R Nah), Postprint (published version)

In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim of preserving significant properties from the original data. Many dimensionality reduction algorithms exist, and nonlinear approaches such as the t-SNE (t-Distributed Stochastic Neighbor Embedding) and UMAP (Uniform Manifold Approximation and Projection) have gained popularity in the field of information visualization. In this paper, we introduce a simple yet powerful manipulation for vector datasets that modifies their values based on weight frequencies. This technique significantly improves the results of the dimensionality reduction algorithms across various scenarios. To demonstrate the efficacy of our methodology, we conduct an analysis on a collection of well-known labeled datasets. The results demonstrate improved clustering performance when attempting to classify the data in the reduced space. Our proposal presents a comprehensive and adaptable approach to enhance the outcomes of dimensionality reduction for visual data exploration., This research was funded by PID2021-122136OB-C21 from the Ministerio de Ciencia e Innovación, Spain, by 839 FEDER (EU) funds., Peer Reviewed, Postprint (published version)

Simulating crowds with realistic behaviors is a difficult but very important task for a variety of applications. Quantifying how a person balances between different conflicting criteria such as goal seeking, collision avoidance and moving within a group is not intuitive, especially if we consider that behaviors differ largely between people. Inspired by recent advances in Deep Reinforcement Learning, we propose Guided REinforcement Learning (GREIL) Crowds, a method that learns a model for pedestrian behaviors which is guided by reference crowd data. The model successfully captures behaviors such as goal seeking, being part of consistent groups without the need to define explicit relationships and wandering around seemingly without a specific purpose. Two fundamental concepts are important in achieving these results: (a) the per agent state representation and (b) the reward function. The agent state is a temporal representation of the situation around each agent. The reward function is based on the idea that people try to move in situations/states in which they feel comfortable in. Therefore, in order for agents to stay in a comfortable state space, we first obtain a distribution of states extracted from real crowd data; then we evaluate states based on how much of an outlier they are compared to such a distribution. We demonstrate that our system can capture and simulate many complex and subtle crowd interactions in varied scenarios. Additionally, the proposed method generalizes to unseen situations, generates consistent behaviors and does not suffer from the limitations of other data-driven and reinforcement learning approaches., This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. This work has received funding from the Spanish Ministry of Science and Innovation (PID2021-122136OB-C21)., Peer Reviewed, Postprint (author's final draft)

Public Bicycle Sharing Systems have spread in many cities for the last decade. The need of analysis tools to predict the behavior or estimate balancing needs has fostered a wide set of approaches that consider many variables. Often, these approaches use a single scenario to evaluate their algorithms, and little is known about the applicability of such algorithms in cities of different sizes. In this paper, we evaluate the performance of widely known prediction algorithms for three sized scenarios: a small system, with around 20 docking stations, a medium-sized one, with 400+ docking stations, and a large one, with more than 1500 stations. The results show that Prophet and Random Forest are the prediction algorithms with more consistent results, and that small systems often have not enough data for the algorithms to perform a solid work., Partially supported by PID2021-122136OB-C21 by Ministerio de Ciencia e Innovación/AEI: (10.13039/501100011033/FEDER, UE), and 2021SGR00613-(ADBD) by Generalitat de Cataluña. The authors would like to thank Logroño City Hall for providing the access to the data., Peer Reviewed, Postprint (published version)

Accurate and reliable human motion reconstruction is crucial for creating natural interactions of full-body avatars in Virtual Reality (VR) and entertainment applications. As the Metaverse and social applications gain popularity, users are seeking cost-effective solutions to create full-body animations that are comparable in quality to those produced by commercial motion capture systems. In order to provide affordable solutions though, it is important to minimize the number of sensors attached to the subject’s body. Unfortunately, reconstructing the full-body pose from sparse data is a heavily under-determined problem. Some studies that use IMU sensors face challenges in reconstructing the pose due to positional drift and ambiguity of the poses. In recent years, some mainstream VR systems have released 6-degree-of-freedom (6-DoF) tracking devices providing positional and rotational information. Nevertheless, most solutions for reconstructing full-body poses rely on traditional inverse kinematics (IK) solutions, which often produce non-continuous and unnatural poses. In this article, we introduce SparsePoser, a novel deep learning-based solution for reconstructing a full-body pose from a reduced set of six tracking devices. Our system incorporates a convolutional-based autoencoder that synthesizes high-quality continuous human poses by learning the human motion manifold from motion capture data. Then, we employ a learned IK component, made of multiple lightweight feed-forward neural networks, to adjust the hands and feet toward the corresponding trackers. We extensively evaluate our method on publicly available motion capture datasets and with real-time live demos. We show that our method outperforms state-of-the-art techniques using IMU sensors or 6-DoF tracking devices, and can be used for users with different body dimensions and proportions., This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie SkŁodowska-Curie grant agreement No 860768 (CLIPE project), HORIZON-CL4-2022-HUMAN-01 grant agreement No 101093159 (XR4ED), and from MCIN/AEI/10.13039/501100011033/FEDER, UE (PID2021-122136OB-C21). This project has also received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. Jose Luis Ponton was also funded by the Spanish Ministry of Universities (FPU21/01927)., Peer Reviewed, Postprint (published version)

Organ transplantation has become very important for treating organ diseases and new technologies have been developed to increase the donor pool. Virtual Reality (VR) has been proven to be a valuable tool for training in medical education. This paper presents a VR application designed to simulate the medical protocol needed for the management of a deceased organ donation process called Uncontrolled Donation after Circulatory determination of Death (uDCD). Results from an explorative study on five medical experts in the area are presented, and future opportunities for improvement are discussed in the paper., Peer Reviewed, Postprint (published version)

One of the key interactions in 3D environments is target acquisition, which can be challenging when targets are small or in cluttered scenes. Here, incorrect elements may be selected, leading to frustration and wasted time. The accuracy is further hindered by the physical act of selection itself, typically involving pressing a button. This action reduces stability, increasing the likelihood of erroneous target acquisition. We focused on molecular visualization and on the challenge of selecting atoms, rendered as small spheres. We present two techniques that improve upon previous progressive selection techniques. They facilitate the acquisition of neighbors after an initial selection, providing a more comfortable experience compared to using classical ray-based selection, particularly with occluded elements. We conducted a pilot study followed by two formal user studies. The results indicated that our approaches were highly appreciated by the participants. These techniques could be suitable for other crowded environments as well., This paper has been supported by TIN2017-88515-C2-1-R (GEN3DLIVE), from the Spanish Ministerio de Economía y Competitividad and PID2021-122136OB-C21 from the Ministerio de Ciencia e Innovación, Spain, by 839 FEDER (EU) funds. Elena Molina has been supported by FI-SDUR doctoral grant from Generalitat de Catalunya, and FPU grant from the Ministerio de Ciencia e Innovación, Spain ., Peer Reviewed, Postprint (published version)

We present a novel proposal for modeling complex dynamic terrains that offers real-time rendering, dynamic updates and physical interaction of entities simultaneously. We can capture any feature from landscapes including tunnels, overhangs and caves, and we can conduct a total destruction of the terrain. Our approach is based on a Constructive Solid Geometry tree, where a set of spheres are subtracted from a base Digital Elevation Model. Erosions on terrain are easily and efficiently carried out with a spherical sculpting tool with pixel-perfect accuracy. Real-time rendering performance is achieved by applying a one-direction CPU–GPU communication strategy and using the standard depth and stencil buffer functionalities provided by any graphics processor., This work has been partially funded by Ministeri de Ciència i Innovació (MICIN), Agencia Estatal de Investigación (AEI) and the Fons Europeu de Desenvolupament Regional (FEDER) (project PID2021-122136OB-C21 funded by MCIN/AEI/10.13039/50110001 1033/FEDER, UE)., Postprint (published version)

In the era of the metaverse, self-avatars are gaining popularity, as they can enhance presence and provide embodiment when a user is immersed in Virtual Reality. They are also very important in collaborative Virtual Reality to improve communication through gestures. Whether we are using a complex motion capture solution or a few trackers with inverse kinematics (IK), it is essential to have a good match in size between the avatar and the user, as otherwise mismatches in self-avatar posture could be noticeable for the user. To achieve such a correct match in dimensions, a manual process is often required, with the need for a second person to take measurements of body limbs and introduce them into the system. This process can be time-consuming, and prone to errors. In this paper, we propose an automatic measuring method that simply requires the user to do a small set of exercises while wearing a Head-Mounted Display (HMD), two hand controllers, and three trackers. Our work provides an affordable and quick method to automatically extract user measurements and adjust the virtual humanoid skeleton to the exact dimensions. Our results show that our method can reduce the misalignment produced by the IK system when compared to other solutions that simply apply a uniform scaling to an avatar based on the height of the HMD, and make assumptions about the locations of joints with respect to the trackers., This work was funded by the Spanish Ministry of Science and Innovation (PID2021-122136OB-C21). Jose Luis Ponton was also funded by the Spanish Ministry of Universities (FPU21/01927)., Peer Reviewed, Postprint (published version)

We present an acceleration structure to efficiently query the Signed Distance Field (SDF) of volumes represented by trianglemeshes. The method is based on a discretization of space. In each node, we store the triangles defining the SDF behaviour inthat region. Consequently, we reduce the cost of the nearest triangle search, prioritizing query performance, while avoidingapproximations of the field. We propose a method to conservatively compute the set of triangles influencing each node. Given anode, each triangle defines a region of space such that all points inside it are closer to a point in the node than the triangle is.This property is used to build the SDF acceleration structure. We do not need to explicitly compute these regions, which is crucialto the performance of our approach. We prove the correctness of the proposed method and compare it to similar approaches,confirming that our method produces faster query times than other exact methods., This work has been partially funded by Ministeri de Ciència i Innovació (MICIN), Agencia Estatal de Investigación (AEI) and the Fons Europeu de Desenvolupament Regional (FEDER) (project PID2021-122136OB-C21 funded by MCIN/AEI/10.13039/501100011033/FEDER, UE). The first author gratefully acknowledges the Universitat Politècnica de Catalunya and Banco Santander for the financial support of his predoctoral grant FPI-UPC grant., Peer Reviewed, Postprint (published version)

In this paper, we present an adaptive structure to represent a signed distance field through trilinear or tricubic interpolation of values, and derivatives, that allows for fast querying of the field. We also provide a method to decide when to subdivide a node to achieve a provided threshold error. Both the numerical error control, and the values needed to build the interpolants, require the evaluation of the input field. Still, both are designed to minimize the total number of evaluations. C0 continuity is guaranteed for both the trilinear and tricubic version of the algorithm. Furthermore, we describe how to preserve C1 continuity between nodes of different levels when using a tricubic interpolant, and provide a proof that this property is maintained. Finally, we illustrate the usage of our approach in several applications, including direct rendering using sphere marching., This work has been partially funded by Ministeri de Ciència i Innovació (MICIN), Agencia Estatal de Investigación (AEI) and the Fons Europeu de Desenvolupament Regional (FEDER) (project PID2021-122136OB-C21 funded by MCIN/AEI/10.13039/501100011033/FEDER, UE). The first author gratefully acknowledges the Universitat Politècnica de Catalunya and Banco Santander for the financial support of his predoctoral grant FPI-UPC grant., Peer Reviewed, Postprint (published version)

Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head-mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments., This work was supported by the US DOE LLNL-LDRD 22-FS- 026 and was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (LLNL-CONF-831245) and by project TIN2017-88515-C2-1-R (GEN3DLIVE), from the Spanish Ministerio de Economía y Competitividad, by 839 FEDER (EU) funds. The work received further support by the French National Research agency (Grant “PIRATE”, ANR-21-CE45-0014) and by the “Initiative d’Excellence” program from the French State (Grant “DYNAMO”, ANR-11-LABX-0011 and grant “CACSICE”, ANR-11-EQPX-0008), and from Carl Zeiss Stiftung. Ministerio de Ciencia e Innovación/AEI (PID2021-122136OB- C21[10.13039/501100011033/FEDER, UE]), Peer Reviewed, Postprint (published version)

Exploring high-dimensional data is a common task in many scientific disciplines. To address this task, two-dimensional embeddings, such as tSNE and UMAP, are widely used. While these determine the 2D position of data items, effectively encoding the first two dimensions, suitable visual encodings can be employed to communicate higher-dimensional features. To investigate such encodings, we have evaluated two commonly used glyph types, namely flower glyphs and star glyphs. To evaluate their capabilities for communicating higher-dimensional features in two-dimensional embeddings, we ran a large set of crowd-sourced user studies using real-world data obtained from data.gov. During these studies, participants completed a broad set of relevant tasks derived from related research. This paper describes the evaluated glyph designs, details our tasks, and the quantitative study setup before discussing the results. Finally, we will present insights and provide guidance on the choice of glyph encodings when exploring high-dimensional data., Peer Reviewed, Postprint (published version)

The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension, Peer Reviewed, Postprint (published version)

This work deals with the automatic 3D reconstruction of objects from frontal RGB images. This aims at a better understanding of the reconstruction of 3D objects from RGB images and their use in immersive virtual environments. We propose a complete workflow that can be easily adapted to almost any other family of rigid objects. To explain and validate our method, we focus on guitars. First, we detect and segment the guitars present in the image using semantic segmentation methods based on convolutional neural networks. In a second step, we perform the final 3D reconstruction of the guitar by warping the rendered depth maps of a fitted 3D template in 2D image space to match the input silhouette. We validated our method by obtaining guitar reconstructions from real input images and renders of all guitar models available in the ShapeNet database. Numerical results for different object families were obtained by computing standard mesh evaluation metrics such as Intersection over Union, Chamfer Distance, and the F-score. The results of this study show that our method can automatically generate high-quality 3D object reconstructions from frontal images using various segmentation and 3D reconstruction techniques., Postprint (published version)

In the last few years the field of Virtual Reality (VR) has experienced significant growth through the introduction of low-cost VR devices to the mass market. However, VR has been used for many years by researchers since it has proven to be a powerful tool across a vast array of research fields and applications. The key aspect of any VR experience is that it is completely immersive, which means that the virtual world totally surrounds the participant. Some game engines such as Unity already support VR out of the box and an application can be configured for VR in a matter of minutes. However, there is still the lack of a standard and easy to use tool in order to embody participants into a virtual human character that responds synchronously to their movements with corresponding virtual body movements. In this paper we introduce QuickVR, a library based on Unity which not only offers embodiment in a virtual character, but also provides a series of high level features that are necessary in any VR application, helping to dramatically reduce the production time. Our tool is easy to use by coding novices, but also easy extensible and customizable by more experienced programmers., Postprint (published version)

Antique paintings are essential to study and understand our past. Paintings, and specifically mural paintings, are delicate artworks that are affected by multiple deterioration conditions. Weathering and human interventions cause different damage problems, and physical and chemical changes degrade their visual color appearance. As a consequence, art historians and archaeologists require a huge effort to attempt to rebuild their original appearance. The annotation of digital images of the paintings is a valuable tool in this process. In this paper we analyze major requirements from art historians concerning the annotation of painting regions from the point of view of digital restoration. We also describe a tool prototype (based on TagLab) intended to facilitate the annotation and segmentation of mural paintings. The tool assists art historians in formulating multiple hypotheses on the original appearance by supporting multiple annotation layers for degradation and color, providing both hand-drawn and semi-automatic segmentation, and offering web-based dissemination and sharing of the annotations through the W3C Web Annotation Data Model., This work has been partially supported by the projects TIN2017-88515-C2-1-R/-2-R funded by MCIN/AEI/ 10.13039/501100011033/ FEDER “A way to make Europe”,by the EUHorizon 2020, JPICH Conservation, Protection and Use initiative (JPICH-0127) and the Spanish Agencia Estatal de Invesigación (grant PCI2020-111979)., Peer Reviewed, Postprint (published version)

The animation of user avatars plays a crucial role in conveying their pose, gestures, and relative distances to virtual objects or other users. Self-avatar animation in immersive VR helps improve the user experience and provides a Sense of Embodiment. However, consumer-grade VR devices typically include at most three trackers, one at the Head Mounted Display (HMD), and two at the handheld VR controllers. Since the problem of reconstructing the user pose from such sparse data is ill-defined, especially for the lower body, the approach adopted by most VR games consists of assuming the body orientation matches that of the HMD, and applying animation blending and time-warping from a reduced set of animations. Unfortunately, this approach produces noticeable mismatches between user and avatar movements. In this work we present a new approach to animate user avatars that is suitable for current mainstream VR devices. First, we use a neural network to estimate the user's body orientation based on the tracking information from the HMD and the hand controllers. Then we use this orientation together with the velocity and rotation of the HMD to build a feature vector that feeds a Motion Matching algorithm. We built a MoCap database with animations of VR users wearing a HMD and used it to test our approach on both self-avatars and other users’ avatars. Our results show that our system can provide a large variety of lower body animations while correctly matching the user orientation, which in turn allows us to represent not only forward movements but also stepping in any direction., This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 860768 (CLIPE project) and the Spanish Ministry of Science and Innovation (PID2021-122136OB-C21)., Peer Reviewed, Postprint (published version)

Research on Visual Computing and Cultural Heritage naturally requires the involvement of multidisciplinary teams comprising art historians and technical experts. Despite the vast literature on digital 3D models in support of Cultural Heritage, the field is so rich and diverse that specific projects often imply distinct, unique requirements which often challenge the computational technologies and suggest new research opportunities. In this paper we discuss the requirements and technical challenges within the EHEM project, an ongoing research program for the analysis, documentation, interpretation, restoration, and communication of medieval artistic heritage. We describe the three monuments that serve as test cases for the project, all of them with a rich history in terms of architecture and paintings. We discuss the art historians' view of how digital models can support their research, the expertise and technological solutions adopted so far, as well as the technical challenges in multiple areas spanning geometry and appearance acquisition, color analysis and restoration as well as the representation of the temporal transformation of the architecture and the paintings., The EHEM project was approved in the JPI Cultural Heritage Conservation, Protection and Use (0127) call in 2020. The JPICH has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 699523. This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy., Peer Reviewed, Postprint (author's final draft)

Smart cities generate a large amount of information that, if used properly, can help improve people's quality of life, while providing environmental support. Decreasing pollution generated by noise, is a prevailing concern, in today's society. A group of experts has collected data in different areas of l'Escaldes-Engordany, in Andorra. These areas have been separated according to traffic policies, i.e., the fully pedestrian ones, the fully vehicular ones, and the combined ones. Analyzing the resulting data may be a complex task, where optimal tools are not available; hence, we have developed a visualization application that allows comparisons and analysis. The main purpose is to improve the conditions in decision making, by having accurate information so that policymakers may have a better understanding of how different transit levels configure the noise landscape, and how contrasting sounds are distributed throughout time. To achieve this, we have developed a visualization application that allows overviewing, detailed individual analysis, and comparative views to parameterize the results of the policies adopted and be in a better position to improve them., Partially supported by project TIN2017-88515-C2-1-R(GEN3DLIVE), from the Spanish Ministerio de Economía y Competitividad, by 839 FEDER (EU) funds. Juan José Franco Moreno is supported by Consejo Nacional de Ciencia y Tecnología (CONACYT, Mexico)., Peer Reviewed, Postprint (published version)

We created a virtual reality version of a 1983 performance by Dire Straits, this being a highly complex scenario consisting of both the virtual band performance and the appearance and behaviour of the virtual audience surrounding the participants. Our goal was to understand the responses of participants, and to learn how this type of scenario might be improved for later reconstructions of other concerts. To understand the responses of participants we carried out two studies which used senti- ment analysis of texts written by the participants. Study 1 (n = 25) (Beacco et al. in IEEE Virtual Reality: 538–545, 2021) had the unexpected finding that negative sentiment was caused by the virtual audience, where e.g. some participants were fearful of being harassed by audience members. In Study 2 (n = 26) notwithstanding some changes, the audience again led to negative sentiment—e.g. a feeling of being stared at. For Study 2 we compared sentiment with questionnaire scores, finding that the illusion of being at the concert was associated with positive sentiment for males but negative for females. Overall, we found sentiment was dominated by responses to the audience rather than the band. Participants had been placed in an unusual situation, being alone at a concert, surrounded by strangers, who seemed to pose a social threat for some of them. We relate our findings to the concept of Plausibility, the illusion that events and situations in the VR are really happening. The results indicate high Plausibility, since the negative sentiment, for example in response to being started at, only makes sense if the events are experienced as actually happening. We conclude with the need for co-design of VR scenarios, and the use of sentiment analysis in this process, rather than sole reliance on concepts proposed by researchers, typically expressed through questionnaires, which may not reflect the experiences of participants., Postprint (published version)

© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., We present a complete automatic system to obtain a realistic 3D avatar reconstruction of a person using only a frontal RGB image. Our proposed workflow first determines the pose, shape and semantic information from the input image. All this information is processed to create the skeleton and the 3D skinned textured mesh that forms the final avatar. We use a specific head reconstruction method to correctly match our final mesh to a realistic avatar. Our pipeline focuses on three main aspects: automation of the process, identification of the person, and usability of the avatar., Postprint (author's final draft)

Sant Quirze de Pedret is a Romanesque church located in Cercs (Catalonia, Spain) at the foothills of the Pyrenees. Its walls harbored one of the most important examples of mural paintings in Catalan Romanesque Art. However, in two different campaigns (in 1921 and 1937) the paintings were removed using the strappo technique and transferred to museums for safekeeping. This detachment protected the paintings from being sold in the art market, but at the price of breaking the integrity of the monument. Nowadays, the paintings are exhibited in the Museu Nacional d'Art de Catalunya - MNAC (Barcelona, Catalonia) and the Museu Diocesà i Comarcal de Solsona - MDCS (Solsona, Catalonia). Some fragments of the paintings are still on the walls of the church. In this work, we present the methodology to digitally reconstruct the church building at its different phases and group the dispersed paintings in a single virtual church, commissioned by the MDCS. We have combined 3D reconstruction (LIDAR and photogrammetric using portable artificial illumination) and modeling techniques (including texture transfer between different shapes) to recover the integrity of the monument in a single 3D virtual model. Furthermore, we have reconstructed the church building at different significant historical moments and placed actual paintings on its virtual walls, based on archaeological knowledge. This set of 3D models allows experts and visitors to better understand the monument as a whole, the relations between the different paintings, and its evolution over time., The project has been promoted by the Museu Diocesà i Comarcal de Solsona (special thanks are due to Carles Freixes and Lídia Fàbregas), co-financed by "La Caixa" Foundation and the Department of Culture of the Generalitat de Catalunya. Likewise, the work presented here counted with the support of MEIC (Spanish Government) project 3D4LIFE (TIN-2017-88515-C2), PRECA II of the Universitat de Barcelona (HAR2017-84451-P) and EHEM (JPICH0127 Conservation, Protection and Use, PCI2020-111979). The high-resolution photographs of the paintings are by Gaetano Alfano (Università degli Studi della Tuscia)., Peer Reviewed, Postprint (published version)

© 2022 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0, The last two decades have exhibited a profound transformation of traditional urban mobility patterns partly due to the exponential growth in both number and popularity of public bicycle sharing systems (BSS). Analysis and visualization of the data generated by BSSs have become of special interest to municipalities to evaluate the effect of their mobility programs and offer integrated urban mobility solutions. In this paper, we present a visualization system that aims to assist city officials from small and medium cities in their decision-making process with an intuitive representation of BSS’ data. It has been developed, tested, and evaluated together with officials and domain experts from the city of Logroño (Spain). Our tool presents usage information with different time granularities (yearly, monthly, weekly, or seasonally), shows traffic flows between stations, and provides an in-depth breakdown of users’ data such as their registered address, traveled distance, or gender-based patterns., Partially supported by project TIN2017-88515-C2-1-R (GEN3DLIVE), from the Spanish Ministerio de Economía y Competitividad, by 839 FEDER (EU) funds. The authors would like to thank Logroño City Hall for providing the access to the data. To Francisco Ridruejo and Jaime Caballero for their invaluable contributions and feedback. To Jordi Masó, from Transports Metropolitans de Girona for providing insights on how they manage the Girocleta system., Peer Reviewed, Postprint (published version)

One way to illustrate distributions of samples is through the use of violin plots. The original design is a combination of boxplot and density plot mirrored and plot around the boxplot. However, there are other designs in literature. Although they seem a powerful way to illustrate distributions, the fact that they encode distributions makes them difficult to read. Users have problems comparing two different distributions, and certain basic statistics such as the mean can be difficult to estimate properly. To get more insights on how people interprets violin plots, we have carried out an experiment to analyze how the different configurations affect judgments over values encoded in those plots., This project has been supported by project TIN2017-88515-C2-1- R(GEN3DLIVE), from the Spanish Ministerio de Economía y Competitividad, by 839 FEDER (EU) funds., Peer Reviewed, Postprint (author's final draft)

Target acquisition is a basic task that is part of almost any high-level interaction in 3D environments. Therefore, providing accurate selection is a necessity for most applications and games. When targets are small and scenes are cluttered, selection becomes inaccurate. This may lead to selecting the wrong elements which, apart from the time consumed, may become a frustrating experience. Besides the unintentional tremor, the button/trigger press for effectively selecting an element further reduces our stability, increasing the probability of an incorrect target acquisition. In this paper, we focus on molecular visualization and address the problem of selecting atoms, which are rendered as small spheres. We build upon previous progressive selection algorithms and present two alternatives that accelerate the selection of neighbors after an initial selection. We have implemented and analyzed such techniques through a formal user study and found that they were highly appreciated by the users. These selection methods may be suitable for other crowded environments beyond molecular visualization., This paper has been supported by TIN2017-88515-C2-1- R (GEN3DLIVE), from the Spanish Ministerio de Economía y Competitividad and PID2021-122136OB-C21 from the Ministerio de Ciencia e Innovación, by 839 FEDER (EU) funds. Elena Molina has been supported by FI-SDUR doctoral grant from Generalitat de Catalunya, and FPU grant from the Ministerio de Ciencia e Innovación., Peer Reviewed, Postprint (published version)

Recent advancements in crowd simulation unravel a wide range of functionalities for virtual agents, delivering highly-realistic,natural virtual crowds. Such systems are of particular importance to a variety of applications in fields such as: entertainment(e.g., movies, computer games); architectural and urban planning; and simulations for sports and training. However, providingtheir capabilities to untrained users necessitates the development of authoring frameworks. Authoring virtual crowds is acomplex and multi-level task, varying from assuming control and assisting users to realise their creative intents, to deliveringintuitive and easy to use interfaces, facilitating such control. In this paper, we present a categorisation of the authorable crowdsimulation components, ranging from high-level behaviours and path-planning to local movements, as well as animation andvisualisation. We provide a review of the most relevant methods in each area, emphasising the amount and nature of influencethat the users have over the final result. Moreover, we discuss the currently available authoring tools (e.g., graphical userinterfaces, drag-and-drop), identifying the trends of early and recent work. Finally, we suggest promising directions for futureresearch that mainly stem from the rise of learning-based methods, and the need for a unified authoring framework., This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska Curie grant agreement No 860768 (CLIPE project). This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy, Peer Reviewed, Postprint (author's final draft)

We review the concept of presence in virtual reality, normally thought of as the sense of “being there” in the virtual world. We argued in a 2009 paper that presence consists of two orthogonal illusions that we refer to as Place Illusion (PI, the illusion of being in the place depicted by the VR) and Plausibility (Psi, the illusion that the virtual situations and events are really happening). Both are with the proviso that the participant in the virtual reality knows for sure that these are illusions. Presence (PI and Psi) together with the illusion of ownership over the virtual body that self-represents the participant, are the three key illusions of virtual reality. Copresence, togetherness with others in the virtual world, can be a consequence in the context of interaction between remotely located participants in the same shared virtual environments, or between participants and virtual humans. We then review several different methods of measuring presence: questionnaires, physiological and behavioural measures, breaks in presence, and a psychophysics method based on transitions between different system configurations. Presence is not the only way to assess the responses of people to virtual reality experiences, and we present methods that rely solely on participant preferences, including the use of sentiment analysis that allows participants to express their experience in their own words rather than be required to adopt the terminology and concepts of researchers. We discuss several open questions and controversies that exist in this field, providing an update to the 2009 paper, in particular with respect to models of Plausibility. We argue that Plausibility is the most interesting and complex illusion to understand and is worthy of significant more research. Regarding measurement we conclude that the ideal method would be a combination of a psychophysical method and qualitative methods including sentiment analysis., Postprint (published version)

The comparison of documents—such as articles or patents search, bibliography recommendations systems, visualization of document collections, etc.—has a wide range of applications in several fields. One of the key tasks that such problems have in common is the evaluation of a similarity metric. Many such metrics have been proposed in the literature. Lately, deep learning techniques have gained a lot of popularity. However, it is difficult to analyze how those metrics perform against each other. In this paper, we present a systematic empirical evaluation of several of the most popular similarity metrics when applied to research articles. We analyze the results of those metrics in two ways, with a synthetic test that uses scientific papers and Ph.D. theses, and in a real-world scenario where we evaluate their ability to cluster papers from different areas of research., This research was funded by Project TIN2017-88515-C2-1-R funded by Ministerio de Economía y Competitividad, under MCIN/AEI/10.13039/501100011033/FEDER “A way to make Europe”., Peer Reviewed, Postprint (published version)

Herb Voelcker and his research team laid the foundations of Solid Modelling, on which Computer-Aided Design is based. He founded the ambitious Production Automation Project, that included Constructive Solid Geometry (CSG) as the basic 3D geometric representation. CSG trees were compact and robust, saving a memory space that was scarce in those times. But the main computational problem was Boundary Evaluation: the process of converting CSG trees to Boundary Representations (BReps) with explicit faces, edges and vertices for manufacturing and visualization purposes. This paper presents some glimpses of the history and evolution of some ideas that started with Herb Voelcker. We briefly describe the path from “localization and boundary evaluation” to “localization and printing”, with many intermediate steps driven by hardware, software and new mathematical tools: voxel and volume representations, triangle meshes, and many others, observing also that in some applications, voxel models no longer require Boundary Evaluation. In this last case, we consider the current research challenges and discuss several avenues for further research., Project TIN2017-88515-C2-1-R funded by MCIN/AEI/10.13039/501100011033/FEDER‘‘A way to make Europe’’, Peer Reviewed, Postprint (published version)

One of the most essential interactions in Virtual Reality (VR) is the user’s ability to move around and explore the virtual environment. The design of the navigation technique plays a crucial role in the user experience since it determines key usability aspects. VR devices allow for an immersive exploration of 3D worlds, but navigation in VR is challenging for many users, due to potential usability issues related to specific VR controllers, user skills, and motion sickness. Although hundreds of interaction techniques have been proposed for this task, VR navigation still poses a high entry barrier for many users. In this paper we argue that adapting the navigation technique to its context of use can lead to substantial improvements in navigation usability and accessibility. The context of use includes the type of scene, the available physical space, as well as the profile of the user. We present a test platform to facilitate the design and fine-tuning of interaction techniques for 3D navigation. We focus on mainstream VR devices (headsets and controllers) and support the most common navigation metaphors (walking, flying, teleportation). The key idea is to let developers specify, at runtime, the exact mapping between user actions and locomotion changes, for any of the supported metaphors. Such mappings are described by a collection of parameters (e.g. maximum speed) whose values can be adjusted interactively through a GUI, or be provided by user-defined code which can be edited at runtime. Feedback obtained from developers suggests that this approach can be used to quickly adapt the navigation techniques to various people including persons with no previous 3D navigation skills, elderly people, and people with disabilities, as well as to the type, size and semantics of the virtual environment., This work has been funded by MCIN/AEI/10.13039/501100011033/FEDER ‘‘A way to make Europe’’. Pedret model partially funded by EU Horizon 2020, JPICH Conservation, Protection and Use initiative (JPICH-0127) and the Spanish Agencia Estatal de Investigación, grant PCI2020-111979 Enhancement of Heritage Experiences: the Middle Ages; Digital Layered Models of Architecture and Mural Paintings over Time (EHEM), Peer Reviewed, Postprint (published version)

View quality measures compute scores for given views and are used to determine an optimal view in viewpoint selection tasks. Unfortunately, despite the wide adoption of these measures, they are rather based on computational quantities, such as entropy, than human preferences. To instead tailor viewpoint measures towards humans, view quality measures need to be able to capture human viewpoint preferences. Therefore, we introduce a large-scale crowdsourced data set, which contains 58k annotated viewpoints for 3220 ModelNet40 models. Based on this data, we derive a neural view quality measure abiding to human preferences. We further demonstrate that this view quality measure not only generalizes to models unseen during training, but also to unseen model categories. We are thus able to predict view qualities for single images, and directly predict human preferred viewpoints for 3D models by exploiting point-based learning technology, without requiring to generate intermediate images or sampling the view sphere. We will detail our data collection procedure, describe the data analysis and model training and will evaluate the predictive quality of our trained viewpoint measure on unseen models and categories. To our knowledge, this is the first deep learning approach to predict a view quality measure solely based on human preferences., This work was supported in part by The Federal Ministry of Education and Research funding program - AuCity 3 - Kollaborative und adaptive Mixed Reality in der Hochschullehre am Beispiel des Bauingenieurwesens, between Magdeburg-Stendal University of Applied Sciences, the Bauhaus University Weimar and Ulm University. Open access funding enabled and organized by Projekt DEAL., Peer Reviewed, Postprint (published version)

High-end Terrestrial Lidar Scanners are often equipped with RGB cameras that are used to colorize the point samples. Some of these scanners produce panoramic HDR images by encompassing the information of multiple pictures with different exposures. Unfortunately, exported RGB color values are not in an absolute color space, and thus point samples with similar reflectivity values might exhibit strong color differences depending on the scan the sample comes from. These color differences produce severe visual artifacts if, as usual, multiple point clouds colorized independently are combined into a single point cloud. In this paper we propose an automatic algorithm to minimize color differences among a collection of registered scans. The basic idea is to find correspondences between pairs of scans, i.e. surface patches that have been captured by both scans. If the patches meet certain requirements, their colors should match in both scans. We build a graph from such pair-wise correspondences, and solve for the gain compensation factors that better uniformize color across scans. The resulting panoramas can be used to colorize the point clouds consistently. We discuss the characterization of good candidate matches, and how to find such correspondences directly on the panorama images instead of in 3D space. We have tested this approach to uniformize color across scans acquired with a Leica RTC360 scanner, with very good results., This work has been partially supported by the project TIN2017-88515-C2-1-R funded by MCIN/AEI/10.13039/5011000- 11033/FEDER ‘‘A way to make Europe’’, by the EU Horizon 2020, JPICH Conservation, Protection and Use initiative (JPICH-0127) and the Spanish Agencia Estatal de Invesigación (grant PCI2020- 111979), by the Universidad Rey Juan Carlos through the Distinguished Researcher position INVESDIST-04 under the call from 17/12/2020, and a Maria Zambrano research fellowship at Universitat Politècnica de Catalunya funded by Ministerio de Universidades., Peer Reviewed, Postprint (published version)