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In their seminal experiment in 1944, Heider and Simmel revealed that humans have a pronounced tendency to impose narrative meaning even in the presence of simple animations of geometric shapes. Despite the shapes having no discernible features or emotions, participants attributed strong social context, meaningful interactions, and even emotions to them. This experiment, run on traditional 2D displays has since had a significant impact on fields ranging from psychology to narrative storytelling. Virtual Reality (VR), on the other hand, offers a significantly new viewing paradigm, a fundamentally different type of experience with the potential to enhance presence, engagement and immersion. In this work, we explore and analyze to what extent the findings of the original experiment by Heider and Simmel carry over into a VR setting. We replicate such experiment in both traditional 2D displays and with a head mounted display (HMD) in VR, and use both subjective (questionnaire-based) and objective (eye-tracking) metrics to record the observers’ visual behavior. We perform a thorough analysis of this data, and propose novel metrics for assessing the observers’ visual behavior. Our questionnaire-based results suggest that participants who viewed the animation through a VR headset developed stronger emotional connections with the geometric shapes than those who viewed it on a traditional 2D screen. Additionally, the analysis of our eye-tracking data indicates that participants who watched the animation in VR exhibited fewer shifts in gaze, suggesting greater engagement with the action. However, we did not find evidence of differences in how subjects perceived the roles of the shapes, with both groups interpreting the animation’s plot at the same level of accuracy. Our findings may have important implications for future psychological research using VR, especially regarding our understanding of social cognition and emotions. [ABSTRACT FROM AUTHOR]

In this article, we address the subject of the recent appearance and exponential and uncontrollable growth that betting had in the Brazilian sports context, alongside numerous changes in the country’s legislation system. Against the backdrop of this growth, we explore the Operation Penalty Kick organised match-fixing scandal, which unravelled in the country, as the media detailed it. Using media sources and field notes from two actors immersed in the field, we analyse the key actors and the processes of the criminal activity while exploring the ways in which it was organised, drawing parallels with trade-type network structures. Through the analysis, we argue that media are to be questioned on their role in (un)covering details of the criminal activity and key actors, once focusing the narrative away from organised crime and its financing they assist in perpetuating the culture of unpunished corruption in the country. [ABSTRACT FROM AUTHOR]

We report an auditory effect of visual performance degradation in a virtual reality (VR) setting, where the viewing conditions are significantly different from previous studies. With the presentation of temporally congruent but spatially incongruent sound, we can degrade visual performance significantly at detection and recognition levels. We further show that this effect is robust to different types and locations of both auditory and visual stimuli. We also analyze participants behavior with an eye tracker to study the underlying cause of the degradation effect. We find that the performance degradation occurs even in the absence of saccades towards the sound source, during normal gaze behavior. This suggests that this effect is not caused by oculomotor phenomena, but rather by neural interactions or attentional shifts. [ABSTRACT FROM AUTHOR]

Non-line-of-sight imaging allows objects to be observed when partially or fully occluded from direct view, by analysing indirect diffuse reflections off a secondary relay surface. Despite many potential applications1–9, existing methods lack practical usability because of limitations including the assumption of single scattering only, ideal diffuse reflectance and lack of occlusions within the hidden scene. By contrast, line-of-sight imaging systems do not impose any assumptions about the imaged scene, despite relying on the mathematically simple processes of linear diffractive wave propagation. Here we show that the problem of non-line-of-sight imaging can also be formulated as one of diffractive wave propagation, by introducing a virtual wave field that we term the phasor field. Non-line-of-sight scenes can be imaged from raw time-of-flight data by applying the mathematical operators that model wave propagation in a conventional line-of-sight imaging system. Our method yields a new class of imaging algorithms that mimic the capabilities of line-of-sight cameras. To demonstrate our technique, we derive three imaging algorithms, modelled after three different line-of-sight systems. These algorithms rely on solving a wave diffraction integral, namely the Rayleigh–Sommerfeld diffraction integral. Fast solutions to Rayleigh–Sommerfeld diffraction and its approximations are readily available, benefiting our method. We demonstrate non-line-of-sight imaging of complex scenes with strong multiple scattering and ambient light, arbitrary materials, large depth range and occlusions. Our method handles these challenging cases without explicitly inverting a light-transport model. We believe that our approach will help to unlock the potential of non-line-of-sight imaging and promote the development of relevant applications not restricted to laboratory conditions. Algorithms based on diffractive wave propagation of light offer effective imaging of complex scenes hidden from direct view. [ABSTRACT FROM AUTHOR]

Selecting an optimal set of icons is a crucial step in the pipeline of visual design to structure and navigate through content. However, designing the icons sets is usually a difficult task for which expert knowledge is required. In this work, to ease the process of icon set selection to the users, we propose a similarity metric which captures the properties of style and visual identity. We train a Siamese Neural Network with an on-line dataset of icons organized in visually coherent collections that are used to adaptively sample training data and optimize the training process. As the dataset contains noise, we further collect human-rated information on the perception of icon's similarity which will be used for evaluating and testing the proposed model. We present several results and applications based on searches, kernel visualizations and optimized set proposals that can be helpful for designers and non-expert users while exploring large collections of icons. [ABSTRACT FROM AUTHOR]

Despite the uniquely high thermal conductivity of graphene is well known, the exploitation of graphene into thermally conductive nanomaterials and devices is limited by the inefficiency of thermal contacts between the individual nanosheets. A fascinating yet experimentally challenging route to enhance thermal conductance at contacts between graphene nanosheets is through molecular junctions, allowing covalently connecting nanosheets, otherwise interacting only via weak Van der Waals forces. Beside the bare existence of covalent connections, the choice of molecular structures to be used as thermal junctions should be guided by their vibrational properties, in terms of phonon transfer through the molecular junction. In this paper, density functional tight-binding combined with Green's functions formalism was applied for the calculation of thermal conductance and phonon spectra of several different aliphatic and aromatic molecular junctions between graphene nanosheets. Effects of molecular junction length, conformation, and aromaticity were studied in detail and correlated with phonon tunnelling spectra. The theoretical insight provided by this work can guide future experimental studies to select suitable molecular junctions, in order to enhance the thermal transport by suppressing the interfacial thermal resistances. This is attractive for various systems, including graphene nanopapers and graphene polymer nanocomposites, as well as related devices. In a broader view, the possibility to design molecular junctions to control phonon transport currently appears as an efficient way to produce phononic devices and controlling heat management in nanostructures. [ABSTRACT FROM AUTHOR]

Searching by style in illustration data sets is a particular problem in Information Retrieval which has received little attention so far. One of its main problems is that the perception of style is highly subjective, which makes labeling styles a very difficult task. Despite being difficult to predict computationally, certain properties such as colorfulness, line style or shading can be successfully captured by existing style metrics. However, there is little knowledge about how we distinguish between different styles and how these metrics can be used to guide users in style-based interactions. In this paper, we propose several contributions towards a better comprehension of illustration style and its usefulness for data exploration and retrieval. First, we provide new insights about how we perceive style in illustration. Second, we evaluate a handmade style clustering of clip art pieces with an existing style metric to analyze how this metric aligns with expert knowledge. Finally, we propose a method for efficient navigation and exploration of large clip art data sets which takes into account both semantic labeling of the data and its style. Our approach combines hierarchical clustering with dimensionality reduction techniques, and strategic sampling to obtain intuitive visualizations and useful visualizations. [ABSTRACT FROM AUTHOR]

We propose a system for creating images of urban scenes composed of the large structures typical in such environments. Our system provides the user with a precomputed library of image-based 3D objects, such as roads, sidewalks and buildings, obtained from a large collection of photographs. When the user picks the 3D location of a new object to insert, the system retrieves objects that have all the required properties (location, orientation and lighting). Then, the user interface guides the user to add more objects enabling non-experts to make a new composition in a fast and intuitive way. Unlike prior work, the entire image composition process is done in the 3D space of the scene, therefore inconsistent scale or perspective distortion does not arise, and occlusions are properly handled. [ABSTRACT FROM AUTHOR]

As the dynamic range of displays keeps increasing, there is a need for reverse tone mapping methods, which aim at expanding the dynamic range of legacy low dynamic range images for viewing on higher dynamic range displays. While a number of strategies have been proposed, most of them are designed for well-exposed input images and are not optimal when dealing with ill-exposed (under- or over-exposed) content. Further, this type of content is more prone to artifacts which may arise when using local methods. In this work, we build on an existing, automatic, global reverse tone mapping operator based on a gamma expansion. We improve this method by providing a new way for automatic parameter calculation from the image statistics. We show that this method yields better results across the whole range of exposures. [ABSTRACT FROM AUTHOR]

In Part I of this two-part series, we examined the design and development of NERVE: A virtual patient simulation created to give medical students standardized experiences in interviewing, examining, and diagnosing virtual patients with cranial nerve disorders. We illustrated key design features and discussed how design-based research studies improved the total learning experience, including the virtual patient (VP) simulations and the instructional features incorporated with the simulations. In Part II, we examine the efficacy of NERVE and the strategy used to integrate the system into the medical school curriculum by field-testing it with 119 s-year medical students, and measuring students' use, reactions, learning, and transfer. We report findings and reflect on lessons learned from the field-test to posit recommendations for improvement and guide the future research and development of virtual patient simulations. [ABSTRACT FROM AUTHOR]

Systematic reviews and meta-analyses of randomized controlled studies conclude that virtual patient simulations are consistently associated with higher learning outcomes compared to other educational methods. However, we cannot assume that students will learn from simply exposing students to the simulations. The instructional features that are integrated before, during and after the simulations may affect learning and performance as much as or more than the simulation and how those features are used. Here, we examine the design and development of NERVE: A virtual patient simulation created to give medical students standardized experiences in interviewing, examining, and diagnosing virtual patients with cranial nerve disorders. We depict key design features of the simulation and discuss how two sets of design research studies were completed to improve the total learning experience, including the virtual patient simulations and the instructional features incorporated with the simulations. [ABSTRACT FROM AUTHOR]

We present a new depth from defocus method based on the assumption that a per pixel blur estimate (related with the circle of confusion), while ambiguous for a single image, behaves in a consistent way when applied over a focal stack of two or more images. This allows us to fit a simple analytical description of the circle of confusion to the different per pixel measures to obtain approximate depth values up to a scale. Our results are comparable to previous work while offering a faster and flexible pipeline. [ABSTRACT FROM AUTHOR]

The phenomenon of birefringence may be observed when light arrives at an anisotropic crystal surface and refracts through it, causing the incident light ray to split into two rays; these become polarized in mutually orthogonal directions, and two images are formed. The principal goal of this paper is the study of the directional issues involved in the behavior of light when refracting through a homogeneous, non-participating medium, including both isotropic and anisotropic media (uniaxial and, for the first time, biaxial). The paper focuses on formulating and solving the non-linear algebraic system that is obtained when the refraction process is simulated using the geometric model of Huygens. The main contribution focuses on the case of biaxial media. In the case of uniaxial media, we rely on symbolic calculus techniques to formulate and solve the problem. [ABSTRACT FROM AUTHOR]

Simulations of models, in all different areas, is an expanding, attractive line of work. More and more applications are taking advantage of the improvements in technology and knowledge in this field, thus achieving results that would have been impossible to achieve with a real model, or foreseeing facts that otherwise would have been encountered too late in the production process. The rail industry is one possible beneficiary of this approach. Usually, before commencing the fabrication process of a new train, the construction of a full-size model is mandatory. Instead of building this full-size real model, which leaves little room for later, last-minute modifications, a virtual model can be built in the digital realm, thus offering a new platform for easier interaction with it. In this article, a simulation of a train is presented in order to tackle visual, aesthetic and ergonomic issues. The simulation runs on a PC-based CAVE-like architecture, offering a certain degree of interaction to the user, and combines static and dynamic computer-generated imagery, both with and without stereoscopy for 3D visualisation, as well as augmented virtuality techniques for the integration of the train with its environment. [ABSTRACT FROM AUTHOR]