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Finding corresponding points between images is a fundamental step in photogrammetry and computer vision tasks. Traditionally, image matching has relied on hand-crafted algorithms such as SIFT or ORB. However, these algorithms face challenges when dealing with multi-temporal images, varying radiometry and contents as well as significant viewpoint differences. Recently, the computer vision community has proposed several deep learning-based approaches that are trained for challenging illumination and wide viewing angle scenarios. However, they suffer from certain limitations, such as rotations, and they are not applicable to high resolution images due to computational constraints. In addition, they are not widely used by the photogrammetric community due to limited integration with standard photogrammetric software packages. To overcome these challenges, this paper introduces Deep-Image-Matching, an open-source toolbox designed to match images using different matching strategies, ranging from traditional hand-crafted to deep-learning methods (https://github.com/3DOM-FBK/deep-image-matching). The toolbox accommodates high-resolution datasets, e.g. data acquired with full-frame or aerial sensors, and addresses known rotation-related problems of the learned features. The toolbox provides image correspondences outcomes that are directly compatible with commercial and open-source software packages, such as COLMAP and openMVG, for a bundle adjustment. The paper includes also a series of cultural heritage case studies that present challenging conditions where traditional hand-crafted approaches typically fail. [ABSTRACT FROM AUTHOR]

In recent years, the digitalization and dissemination of historical heritage have become crucial nodes in the preservation and valorization of Cultural Heritage (CH). Technologies such as Unmanned Aerial Vehicle (UAV) and terrestrial photogrammetry, Terrestrial Laser Scanning (TLS) and handheld Simultaneous Localisation and Mapping (SLAM) laser scanning allow the generation of digital models of architecture that can be explored through interactive web platforms, such as those based on WebGL graphic library. These are considered one of the most promising innovations for digitizing and sharing CH site due to their application in a wide range of contexts, promoting new forms of interaction with architecture at different scales. Additionally, the use of geomatic tools allows for a more complete 3D reconstruction and evaluation of the results by comparing different techniques. The article focuses on digitization as a tool for documenting and sharing CH assets, with the aim of developing a replicable prototype platform for an immersive Virtual Tour (VT) of an art collection and the architectural complex in which it is resided. In addition, this paper presents the results of a case study conducted at the Ricci Oddi Gallery of Modern Art in Piacenza, Italy. The source code of the implemented application is available on GitHub to permit replicability for other case studies. [ABSTRACT FROM AUTHOR]

The adoption of open-source mobile mapping applications in public administration has risen over the last decade due to their interdisciplinary vocation and flexibility in adapting to existing Geographic Information System (GIS) software architectures. This facilitates complex procedures of data collection and management required for transportation and environmental models, emergency management, and maintenance operations. The Ministry of Infrastructure and Transport in Italy requires road-owning agencies to build and maintain a mapping inventory of their road networks, including georeferenced information about streets and ancillary elements, such as traffic signs. Innovative and integrated street-level approaches for the rapid mapping of road entities using open-source mobile mapping tools represent a valuable low-cost solution for the periodical update of road entities inventory. The adoption of these tools allows public administrators to easily consult the road inventory even outside the office, conducting in situ validation and quality evaluation. This work presents a case study focused on the update and management of traffic sign entities of the Road Cadastre of the Province of Piacenza (Italy) using Qfield and Open Data Kit (ODK) Collect as alternatives to the previous traditional survey method that consisted in the use of field papers. A comparison between the adoption of the two mobile apps is conducted, identifying benefits and limitations in terms of both data accuracy and usability. Validation scripts, project and form structure were developed with the perspective of making the entire workflow as reproducible and transparent as possible, sharing details in a dedicated GitHub repository. [ABSTRACT FROM AUTHOR]

Georeferenced reconstructions can help understand the dynamic evolution of the urban context surrounding a historical site, supporting decision-making processes in the field of urban planning. The development of web applications that allow the interaction between 2D and 3D products, as well as their exploration, can facilitate virtual inspections and foster collaboration in digitization of interventions and site evolutions over time. The article discusses how virtual scene reconstructions and visits can provide alternatives to traditional in-situ tourism promotion, through digital storytelling solutions for the exploration of sites. The article also describes how 3D storytelling technologies are currently being used for dissemination cultural heritage sites. The case study of the Castello Farnese, an old XVI century heritage site in Piacenza (Italy), test the adoption of two distinct free and open-source JavaScript WebGL, Potree and Cesium, for the rendering of photogrammetric and laser scanning georeferenced scaled products and for the integration of narrative features such as annotations, camera animations, texts, and other multimedia contents. Potentials and limitations of both tools are discussed in detail, highlighting how they can be implemented for enhancing user experience in virtual tour and exploration of 3D products. In order to guarantee replicability for other case studies, source code of the implemented application is shared on GitHub along with its documentation for contributions. [ABSTRACT FROM AUTHOR]

SLAM technology is more and more integrated with other sensors for indoor and outdoor seamless navigation. This research topic is very active in particular on image matching with deep learning local features, keyframe selection approaches, or tests on new IMU and GNSS solutions. Integrating and testing new methodologies on other widely used SLAM implementations, such as ORB-SLAM, can be not a trivial task. Therefore, we propose an extension of COLMAP to be used in real-time as a feature-based Visual-SLAM that can be also coupled with other sensors. COLMAP has been chosen due to its modularity and the large community that assures the continuity of the repository. The paper presents a pipeline mainly thought for real-time evaluation of learning-based tie points and new SLAM features, that works with both monocular, stereo and multi-camera systems. It is also shown an example of keyframe selection algorithm based on deep learning local features, and a simple example of IMU integration. The code is available on the GitHub repository https://github.com/3DOM-FBK/COLMAP_SLAM. [ABSTRACT FROM AUTHOR]

Image-based monitoring has emerged as a prevalent technique for sensing mountain environments. Monoscopic time-lapse cameras, which rely on digital image correlation to quantify glacier motion, have limitations due to the need for a Digital Elevation Model for deriving 3D flow velocity fields. Multi-camera systems overcome this limitation, as they allow for a 3D reconstruction of the scene. This paper presents a replicable low-cost stereoscopic system designed for 4D glacier monitoring. The system consists of independent and autonomous units, built from off-the-shelves components, such as a DSLR camera, an Arduino microcontroller, and a Raspberry Pi Zero, reducing costs compared to pre-built time-lapse cameras. The units are energetically self-sufficient and resistant to harsh alpine conditions. The system was successfully tested for more than a year to monitor the northwest terminus of the Belvedere Glacier (Italian Alps). Daily stereo-pairs acquired were processed with Structure-from-Motion to derive 3D point clouds of the glacier terminus and estimate glacier retreat and ice volume loss. By combining the information about ice volume loss with ablation estimates and ice flow velocity information, e.g., derived from monoscopic-camera time series, a multi-camera system enables a comprehensive understanding of sub-seasonal glacier dynamics. [ABSTRACT FROM AUTHOR]

The health assessment of strategic infrastructures and bridges represents a critical variable for planning appropriate maintenance operations. The high costs and complexity of traditional periodical monitoring with elevating platforms have driven the search for more efficient and flexible methods. Indeed, recent years have seen the growing diffusion and adoption of non-invasive approaches consisting in the use of Unmanned Aerial Vehicles (UAVs) for applications that range from visual inspection with optical sensors to LiDAR technologies for rapid mapping of the territory. This study defines two different methodologies for bridge inspection. A first approach involving the integration of traditional topographic and GNSS techniques with TLS and photogrammetry with cameras mounted on UAV was compared with a UAV-LiDAR method based on the use of a DJI Matrice 300 equipped with a LiDAR DJI Zenmuse L1 sensor for a manual flight and an automatic one. While the first workflow resulted in a centimetric accurate but time-consuming model, the UAV-LiDAR resulting point cloud's georeferencing accuracy resulted to be less accurate in the case of the manual flight under the bridge for GNSS signal obstruction. However, a photogrammetric model reconstruction phase made with Ground Control Points and photos taken by the L1-embedded camera improved the overall accuracy of the workflow, that could be employed for flexible low-cost mapping of bridges when medium level accuracy (5–10 cm) is accepted. In conclusion, a solution for integrating interactively final 3D products in a Bridge Management System environment is presented. [ABSTRACT FROM AUTHOR]

Monitoring cracks opening on concrete bridges is a key aspect for structural health assessment. Digital image processing, combined with Unmanned Aerial Vehicles (UAVs) and photogrammetry, allows for non-contact 3D reconstruction of cracks, reducing costs and potential unsafe factors involved in manual inspections. This paper presents a flexible procedure based on UAV photogrammetry for accurate evaluation of cracks geometry, that can be implemented for periodic structural monitoring. Stereo-pair of images, acquired with UAVs close to the cracked surface, are used to build a scaled photogrammetric model through Structure-from-Motion. Cracks are detected on images by image binarization and digital image processing techniques. Thereafter, one single image is used to reconstruct crack 3D geometry, by back-projecting crack image coordinates on a 3D model of the object. This can be built from the current stereo-pair of images, or based on an existing photogrammetric model, in the case of a periodic monitoring set-up. Crack width is accurately estimated in 3D world. The procedure is tested and evaluated in a case study, obtaining millimetric accurate results, which is in line with the average ground sample distance of the images employed. Results highlight the potentials of UAVs and photogrammetry not only for bridge inspections and damages localization, but also for accurately evaluating cracks geometry and helping structural engineers to assess structure health conditions. [ABSTRACT FROM AUTHOR]

Traditional flow velocity measurements in natural environments require contact with the fluid and are usually costly, time-consuming and, sometimes, even dangerous. Particle Image Velocimetry allows the flow velocity field to be remotely characterized from the shift of intensity patterns of sub-image areas in at least two video frames with a known time lag. Recently, Airborne Image Velocimetry has enabled the surface velocity field of large-scale water bodies to be determined by applying Particle Image Velocimetry on videos recorded by cameras mounted on unmanned aerial vehicles. This work presents a comparison of three Airborne Image Velocimetry approaches: BASESURV, Fudaa-LSPIV and RIVeR. For the evaluation, two nadiral videos were acquired with a low-cost quadcopter. The first was recorded under low flow and seeded conditions, the second during a flood event. According to the results obtained, BASESURV is an accurate and complete research oriented approach but it is time-consuming and neither a graphical interface nor documentation are yet provided. Fudaa-LSPIV is a well-developed software package, with a user-friendly graphical interface and good documentation. However it lacks some features and the source code is closed. RIVeR may be suitable for real time monitoring thanks to the rectification of velocity vectors only. Overall, all the codes are found to be effective in performing Airborne Image Velocimetry in riverine environments. [ABSTRACT FROM AUTHOR]

Background Studies on the inflammatory process in the large airways of patients with mild/moderate COPD have shown a prevalent T lymphocyte and macrophage infiltration of the bronchial mucosa. However, bronchial inflammation in more severe disease has not been extensively studied. Objective The aim of the present study was to characterize the lymphocyte infiltration in the bronchial mucosa of subjects with severe, compared to mild, COPD, and to examine the relationship between airflow limitation and T lymphocyte numbers in the bronchial mucosa. Methods We examined bronchial biopsies obtained from nine smokers with severe airflow limitation, nine smokers with mild/moderate airflow limitation and 14 smokers with normal lung function. Immunohistochemical methods on cryostat sections were used to assess the number of CD3+, CD4+, CD8+ cells and the number of CD3+ cells coexpressing the chemokine receptor CCR5 (CCR5+CD3+) in the subepithelium. Results Subjects with severe COPD had lower numbers of CD3+, CD8+ and CCR5+CD3+ cells than mild/moderate COPD (P < 0.012, P < 0.02 and P < 0.02, respectively) and control smokers (P < 0.015, P < 0.005 and P < 0.015, respectively). In subjects with airflow limitation the number of CD3+ and CD8+ cells was inversely correlated with the degree of airway obstruction (r = 0.59, P < 0.015 and r = 0.52, P < 0.032, respectively). Conclusions Bronchial inflammation in severe COPD is characterized by lower numbers of CD3+ and CD8+ cells and decreased numbers of CD3+ cells coexpressing the chemokine receptor CCR5. T lymphocyte infiltration is inversely correlated with the degree of airflow limitation. [ABSTRACT FROM AUTHOR]