Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-289-2024
C. Mulsow, H. Sardemann, Laure-Anne Gueguen, Gottfried Mandelburger, Hans-Gerd Maas
Abstract. A common problem when imaging and measuring through moving water surfaces is the quasi-random refraction caused by waves. The article presents two strategies to overcome this problem by lowering the complexity down to a planer air/water interface problem. In general, the methods assume that the shape of the water surface changes randomly over time and that the water surface moves around an idle-state (calm planar water surface). Thus, moments at which the surface normal is orientated vertically should occur more frequently than others should. By analysing a sequence of images taken from a stable camera position these moments could be identified – this can be done in the image or object space. It will be shown, that a simple median filtering of grey values in each pixel position can provide a corrected image freed from wave and glint effects. This should have the geometry of an image taken through calm water surface. However, in case of multi camera setups, the problem can be analysed in object space. By tracking homological underwater features, sets of image rays hitting accidently horizontal orientated water surface areas can be identified. Both methods are described in depth and evaluated on real and simulated data.
{"title":"Concepts for compensation of wave effects when measuring through water surfaces in photogrammetric applications","authors":"C. Mulsow, H. Sardemann, Laure-Anne Gueguen, Gottfried Mandelburger, Hans-Gerd Maas","doi":"10.5194/isprs-archives-xlviii-2-2024-289-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-289-2024","url":null,"abstract":"Abstract. A common problem when imaging and measuring through moving water surfaces is the quasi-random refraction caused by waves. The article presents two strategies to overcome this problem by lowering the complexity down to a planer air/water interface problem. In general, the methods assume that the shape of the water surface changes randomly over time and that the water surface moves around an idle-state (calm planar water surface). Thus, moments at which the surface normal is orientated vertically should occur more frequently than others should. By analysing a sequence of images taken from a stable camera position these moments could be identified – this can be done in the image or object space. It will be shown, that a simple median filtering of grey values in each pixel position can provide a corrected image freed from wave and glint effects. This should have the geometry of an image taken through calm water surface. However, in case of multi camera setups, the problem can be analysed in object space. By tracking homological underwater features, sets of image rays hitting accidently horizontal orientated water surface areas can be identified. Both methods are described in depth and evaluated on real and simulated data.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"31 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141355479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-73-2024
F. Condorelli, Maurizio Perticarini
Abstract. The reconstruction of three-dimensional scenes from a single image represents a significant challenge in computer vision, particularly in the context of cultural heritage digitisation, where datasets may be limited or of poor quality. This paper addresses this challenge by conducting a study of the latest and most advanced algorithms for single-image 3D reconstruction, with a focus on applications in cultural heritage conservation. Exploiting different single-image datasets, the research evaluates the strengths and limitations of various artificial intelligence-based algorithms, in particular Neural Radiance Fields (NeRF), in reconstructing detailed 3D models from limited visual data. The study includes experiments on scenarios such as inaccessible or non-existent heritage sites, where traditional photogrammetric methods fail. The results demonstrate the effectiveness of NeRF-based approaches in producing accurate, high-resolution reconstructions suitable for visualisation and metric analysis. The results contribute to advancing the understanding of NeRF-based approaches in handling single-image inputs and offer insights for real-world applications such as object location and immersive content generation.
{"title":"Comparative Evaluation of NeRF Algorithms on Single Image Dataset for 3D Reconstruction","authors":"F. Condorelli, Maurizio Perticarini","doi":"10.5194/isprs-archives-xlviii-2-2024-73-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-73-2024","url":null,"abstract":"Abstract. The reconstruction of three-dimensional scenes from a single image represents a significant challenge in computer vision, particularly in the context of cultural heritage digitisation, where datasets may be limited or of poor quality. This paper addresses this challenge by conducting a study of the latest and most advanced algorithms for single-image 3D reconstruction, with a focus on applications in cultural heritage conservation. Exploiting different single-image datasets, the research evaluates the strengths and limitations of various artificial intelligence-based algorithms, in particular Neural Radiance Fields (NeRF), in reconstructing detailed 3D models from limited visual data. The study includes experiments on scenarios such as inaccessible or non-existent heritage sites, where traditional photogrammetric methods fail. The results demonstrate the effectiveness of NeRF-based approaches in producing accurate, high-resolution reconstructions suitable for visualisation and metric analysis. The results contribute to advancing the understanding of NeRF-based approaches in handling single-image inputs and offer insights for real-world applications such as object location and immersive content generation.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"1 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141356483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-9-2024
R. Arav, C. Ressl, Robert Weiss, Thomas Artz, Gottfried Mandlburger
Abstract. The eulittoral zone, which alternates between being exposed and submerged, presents a challenge for high-resolution characterization. Normally, its mapping is divided between low and high water levels, where each calls for a different type of surveying instrument. This leads to inconsistent mapping products, both in accuracy and resolution. Recently, uncrewed airborne vehicle (UAV) based photogrammetry was suggested as an available and low-cost solution. However, relying on a passive sensor, this approach requires adequate environmental conditions, while its ability to map inundated regions is limited. Alternatively, UAV-based topo-bathymetric laser scanners enable the acquisition of both submerged and exposed regions independent of lighting conditions while maintaining the acquisition flexibility. In this paper, we evaluate the applicability of such systems in the eulittoral zone. To do so, both topographic and topo-bathymetric LiDAR sensors were loaded on UAVs to map a coastal region along the river Rhein. The resulting point clouds were compared to UAV-based photogrammetric ones. Aspects such as point spacing, absolute accuracy, and vertical offsets were analysed. To provide operative recommendations, each LiDAR scan was acquired at different flying altitudes, while the photogrammetric point clouds were georeferenced based on different exterior information configurations. To assess the riverbed modelling, we compared the surface model acquired by the topo-bathymetric LiDAR sensor to multibeam echosounder measurements. Our analysis shows that the accuracies of the LiDAR point clouds are hardly affected by flying altitude. The derived riverbed elevation, on the other hand, shows a bias which is linearly related to water depth.
{"title":"Evaluation of Active and Passive UAV-Based Surveying Systems for Eulittoral Zone Mapping","authors":"R. Arav, C. Ressl, Robert Weiss, Thomas Artz, Gottfried Mandlburger","doi":"10.5194/isprs-archives-xlviii-2-2024-9-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-9-2024","url":null,"abstract":"Abstract. The eulittoral zone, which alternates between being exposed and submerged, presents a challenge for high-resolution characterization. Normally, its mapping is divided between low and high water levels, where each calls for a different type of surveying instrument. This leads to inconsistent mapping products, both in accuracy and resolution. Recently, uncrewed airborne vehicle (UAV) based photogrammetry was suggested as an available and low-cost solution. However, relying on a passive sensor, this approach requires adequate environmental conditions, while its ability to map inundated regions is limited. Alternatively, UAV-based topo-bathymetric laser scanners enable the acquisition of both submerged and exposed regions independent of lighting conditions while maintaining the acquisition flexibility. In this paper, we evaluate the applicability of such systems in the eulittoral zone. To do so, both topographic and topo-bathymetric LiDAR sensors were loaded on UAVs to map a coastal region along the river Rhein. The resulting point clouds were compared to UAV-based photogrammetric ones. Aspects such as point spacing, absolute accuracy, and vertical offsets were analysed. To provide operative recommendations, each LiDAR scan was acquired at different flying altitudes, while the photogrammetric point clouds were georeferenced based on different exterior information configurations. To assess the riverbed modelling, we compared the surface model acquired by the topo-bathymetric LiDAR sensor to multibeam echosounder measurements. Our analysis shows that the accuracies of the LiDAR point clouds are hardly affected by flying altitude. The derived riverbed elevation, on the other hand, shows a bias which is linearly related to water depth.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"52 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141358549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-55-2024
M. A. Cherif, S. Tripodi, Y. Tarabalka, Isabelle Manighetti, L. Laurore
Abstract. The surge in data across diverse fields presents an essential need for advanced techniques to merge and interpret this information. With a special emphasis on compiling geospatial data, this integration is crucial for unlocking new insights from geographic data, enhancing our ability to map and analyze trends that span across different locations and environments with more authenticity and reliability. Existing techniques have made progress in addressing data fusion; however, challenges persist in fusing and harmonizing data from different sources, scales, and modalities. This research presents a comprehensive investigation into the challenges and solutions in vector map alignment, focusing on developing methods that enhance the precision and usability of geospatial data. We explored and developed three distinct methodologies for polygonal vector map alignment: ProximityAlign, which excels in precision within urban layouts but faces computational challenges; the Optical Flow Deep Learning-Based Alignment, noted for its efficiency and adaptability; and the Epipolar Geometry-Based Alignment, effective in data-rich contexts but sensitive to data quality. In practice, the proposed approaches serve as tools to benefit from as much as possible from existing datasets while respecting a spatial reference source. It also serves as a paramount step for the data fusion task to reduce its complexity.
{"title":"Novel Approaches for Aligning Geospatial Vector Maps","authors":"M. A. Cherif, S. Tripodi, Y. Tarabalka, Isabelle Manighetti, L. Laurore","doi":"10.5194/isprs-archives-xlviii-2-2024-55-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-55-2024","url":null,"abstract":"Abstract. The surge in data across diverse fields presents an essential need for advanced techniques to merge and interpret this information. With a special emphasis on compiling geospatial data, this integration is crucial for unlocking new insights from geographic data, enhancing our ability to map and analyze trends that span across different locations and environments with more authenticity and reliability. Existing techniques have made progress in addressing data fusion; however, challenges persist in fusing and harmonizing data from different sources, scales, and modalities. This research presents a comprehensive investigation into the challenges and solutions in vector map alignment, focusing on developing methods that enhance the precision and usability of geospatial data. We explored and developed three distinct methodologies for polygonal vector map alignment: ProximityAlign, which excels in precision within urban layouts but faces computational challenges; the Optical Flow Deep Learning-Based Alignment, noted for its efficiency and adaptability; and the Epipolar Geometry-Based Alignment, effective in data-rich contexts but sensitive to data quality. In practice, the proposed approaches serve as tools to benefit from as much as possible from existing datasets while respecting a spatial reference source. It also serves as a paramount step for the data fusion task to reduce its complexity.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"89 25","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141359500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-81-2024
Corentin Dufourg, Charlotte Pelletier, Stéphane May, Sébastien Lefèvre
Abstract. In the context of climate change, it is important to monitor the dynamics of the Earth’s surface in order to prevent extreme weather phenomena such as floods and droughts. To this end, global meteorological forecasting is constantly being improved, with a recent breakthrough in deep learning methods. In this paper, we propose to adapt a recent weather forecasting architecture, called GraphCast, to a water resources forecasting task using high-resolution satellite image time series (SITS). Based on an intermediate mesh, the data geometry used within the network is adapted to match high spatial resolution data acquired in two-dimensional space. In particular, we introduce a predefined irregular mesh based on a segmentation map to guide the network’s predictions and bring more detail to specific areas. We conduct experiments to forecast water resources index two months ahead on lakes and rivers in Italy and Spain. We demonstrate that our adaptation of GraphCast outperforms the existing frameworks designed for SITS analysis. It also showed stable results for the main hyperparameter, i.e., the number of superpixels. We conclude that adapting global meteorological forecasting methods to SITS settings can be beneficial for high spatial resolution predictions.
{"title":"Forecasting water resources from satellite image time series using a graph-based learning strategy","authors":"Corentin Dufourg, Charlotte Pelletier, Stéphane May, Sébastien Lefèvre","doi":"10.5194/isprs-archives-xlviii-2-2024-81-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-81-2024","url":null,"abstract":"Abstract. In the context of climate change, it is important to monitor the dynamics of the Earth’s surface in order to prevent extreme weather phenomena such as floods and droughts. To this end, global meteorological forecasting is constantly being improved, with a recent breakthrough in deep learning methods. In this paper, we propose to adapt a recent weather forecasting architecture, called GraphCast, to a water resources forecasting task using high-resolution satellite image time series (SITS). Based on an intermediate mesh, the data geometry used within the network is adapted to match high spatial resolution data acquired in two-dimensional space. In particular, we introduce a predefined irregular mesh based on a segmentation map to guide the network’s predictions and bring more detail to specific areas. We conduct experiments to forecast water resources index two months ahead on lakes and rivers in Italy and Spain. We demonstrate that our adaptation of GraphCast outperforms the existing frameworks designed for SITS analysis. It also showed stable results for the main hyperparameter, i.e., the number of superpixels. We conclude that adapting global meteorological forecasting methods to SITS settings can be beneficial for high spatial resolution predictions.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"16 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141355886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-41-2024
Liam Boyle, P. Helmholz, D. Lichti, Roslyn Ward
Abstract. The term speech sound disorder describes a range of speech difficulties in children that affect speech intelligibility. Differential diagnosis is difficult and reliant on access to validated and reliable measures. Technological advances aim to provide clinical access to measurements that have been identified as beneficial in diagnosing speech disorders. To generate objective measurements and, consequently, automatic scores, the output from multi-camera networks is required to produce quality results. The quality of photogrammetric results is usually expressed in terms of the precision and reliability of the network. Precision is determined at the design stage as a function of the geometry of the network. In this manuscript, we focus on the design of a photogrammetric camera network using three cameras. We adopted a similar workflow as Alsadika et al. (2012) and tested serval network configurations. As the distances from the camera stations to object points were fixed to 3500mm, only the horizontal and vertical placements of the cameras were varied. Horizontal angles were changed within an increment of 10º, and vertical angles were changed within an increment of 5º. The object space coordinates of GCPs for each camera configuration were assessed in terms of horizontal error ellipses and vertical precision. The best design was the maximum horizontal and vertical convergence angles of 90° and 30°. The existing camera network used to capture videos for speech assessment was approximately as good as the top third of tested designs. However, from a validation perspective, it can be concluded that the design is viable for continued use.
{"title":"Validation of Camera Networks Used for the Assessment of Speech Movements","authors":"Liam Boyle, P. Helmholz, D. Lichti, Roslyn Ward","doi":"10.5194/isprs-archives-xlviii-2-2024-41-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-41-2024","url":null,"abstract":"Abstract. The term speech sound disorder describes a range of speech difficulties in children that affect speech intelligibility. Differential diagnosis is difficult and reliant on access to validated and reliable measures. Technological advances aim to provide clinical access to measurements that have been identified as beneficial in diagnosing speech disorders. To generate objective measurements and, consequently, automatic scores, the output from multi-camera networks is required to produce quality results. The quality of photogrammetric results is usually expressed in terms of the precision and reliability of the network. Precision is determined at the design stage as a function of the geometry of the network. In this manuscript, we focus on the design of a photogrammetric camera network using three cameras. We adopted a similar workflow as Alsadika et al. (2012) and tested serval network configurations. As the distances from the camera stations to object points were fixed to 3500mm, only the horizontal and vertical placements of the cameras were varied. Horizontal angles were changed within an increment of 10º, and vertical angles were changed within an increment of 5º. The object space coordinates of GCPs for each camera configuration were assessed in terms of horizontal error ellipses and vertical precision. The best design was the maximum horizontal and vertical convergence angles of 90° and 30°. The existing camera network used to capture videos for speech assessment was approximately as good as the top third of tested designs. However, from a validation perspective, it can be concluded that the design is viable for continued use.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"19 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141360443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-1-2024
Simon Albers, R. Rofallski, Paul-Felix Hagen, T. Luhmann
Abstract. Rubber production is a labour-intensive process. In order to reduce the needed number of workers and the waste of material, the level of digitalisation should be increased. One part of the production is the extrusion to produce gaskets and similar objects. An automated observation of the continuous rubber extrudate enables an early intervention in the production process. In addition to chemical monitoring, the geometrical observation of the extrudate is an important aspect of the quality control. For this purpose, we use laser triangulation sensors (LTS) at the beginning and the end of the cooling phase of the extrudate after the extrusion. The LTS acquire two-dimensional profiles at a constant frequency. To combine these profiles into a three-dimensional model of the extrudate, the movement of the extrudate has to be tracked. Since the extrudate is moved over a conveyor belt, the conveyor belt can be tracked by a stereo camera system to deduce the movement of the extrudate. For the correct usage of the tracking, the orientation between the LTS and the stereo camera system needs to be known. A calibration object that considers the different data from the LTS and the camera system was developed to determine the orientation. Afterwards, the orientation can be used to combine arbitrary profiles. The measurement setup, consisting of the LTS, the stereo camera system and the conveyor belt, is explained. The development of the calibration object, the algorithm for evaluating the orientation data and the combination of the LTS profiles are described. Finally, experiments with real extrusion data are presented to validate the results and compare three variations of data evaluation. Two use the calculated orientation, but have different tracking approaches and one without any orientation necessary.
{"title":"Procedure for the Orientation of Laser Triangulation Sensors to a Stereo Camera System for the Inline Measurement of Rubber Extrudate","authors":"Simon Albers, R. Rofallski, Paul-Felix Hagen, T. Luhmann","doi":"10.5194/isprs-archives-xlviii-2-2024-1-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-1-2024","url":null,"abstract":"Abstract. Rubber production is a labour-intensive process. In order to reduce the needed number of workers and the waste of material, the level of digitalisation should be increased. One part of the production is the extrusion to produce gaskets and similar objects. An automated observation of the continuous rubber extrudate enables an early intervention in the production process. In addition to chemical monitoring, the geometrical observation of the extrudate is an important aspect of the quality control. For this purpose, we use laser triangulation sensors (LTS) at the beginning and the end of the cooling phase of the extrudate after the extrusion. The LTS acquire two-dimensional profiles at a constant frequency. To combine these profiles into a three-dimensional model of the extrudate, the movement of the extrudate has to be tracked. Since the extrudate is moved over a conveyor belt, the conveyor belt can be tracked by a stereo camera system to deduce the movement of the extrudate. For the correct usage of the tracking, the orientation between the LTS and the stereo camera system needs to be known. A calibration object that considers the different data from the LTS and the camera system was developed to determine the orientation. Afterwards, the orientation can be used to combine arbitrary profiles. The measurement setup, consisting of the LTS, the stereo camera system and the conveyor belt, is explained. The development of the calibration object, the algorithm for evaluating the orientation data and the combination of the LTS profiles are described. Finally, experiments with real extrusion data are presented to validate the results and compare three variations of data evaluation. Two use the calculated orientation, but have different tracking approaches and one without any orientation necessary.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"76 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141359825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-409-2024
Alex Spengler, K. Pascoe, C. Kapono, Haunani H. Kane, John Burns
Abstract. Coral reefs and submerged cultural heritage sites are integral to supporting marine biodiversity, preserving human history, providing ecosystem services, and understanding drivers of ecosystem health and function. Despite the importance of these submerged underwater habitats, accessibility to these environments remains limited to specialized professionals. The MEGA Vision mixed reality application integrates photogrammetry-derived data products with augmented reality (AR) technologies to transcend this barrier, offering an immersive and educational platform for the broader public. Using high-resolution imagery from SCUBA expeditions, the app presents users with realistic and spatially accurate 3D reconstructions of coral reefs and submerged archaeological artifacts within an interactive interface developed through Unity and Vuforia. The applications’ instructional design includes multimedia elements for enhancing user comprehension of marine and historical sciences. This mixed reality tool exemplifies the convergence of scientific data visualization and public engagement, offering a unique educational tool that demystifies the complexities of marine ecosystems and maritime history, thereby fostering a deeper appreciation and stewardship of underwater environments. By enabling accessible, interactive, and immersive experiences, the application has the potential to revolutionize the way we interact with and contribute to marine sciences, aligning technology with conservation and research efforts to cultivate a more informed and environmentally conscious public.
{"title":"MEGA Vision: Integrating Reef Photogrammetry Data into Immersive Mixed Reality Experiences","authors":"Alex Spengler, K. Pascoe, C. Kapono, Haunani H. Kane, John Burns","doi":"10.5194/isprs-archives-xlviii-2-2024-409-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-409-2024","url":null,"abstract":"Abstract. Coral reefs and submerged cultural heritage sites are integral to supporting marine biodiversity, preserving human history, providing ecosystem services, and understanding drivers of ecosystem health and function. Despite the importance of these submerged underwater habitats, accessibility to these environments remains limited to specialized professionals. The MEGA Vision mixed reality application integrates photogrammetry-derived data products with augmented reality (AR) technologies to transcend this barrier, offering an immersive and educational platform for the broader public. Using high-resolution imagery from SCUBA expeditions, the app presents users with realistic and spatially accurate 3D reconstructions of coral reefs and submerged archaeological artifacts within an interactive interface developed through Unity and Vuforia. The applications’ instructional design includes multimedia elements for enhancing user comprehension of marine and historical sciences. This mixed reality tool exemplifies the convergence of scientific data visualization and public engagement, offering a unique educational tool that demystifies the complexities of marine ecosystems and maritime history, thereby fostering a deeper appreciation and stewardship of underwater environments. By enabling accessible, interactive, and immersive experiences, the application has the potential to revolutionize the way we interact with and contribute to marine sciences, aligning technology with conservation and research efforts to cultivate a more informed and environmentally conscious public.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"89 26","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141359499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-379-2024
Vandita Shukla, Luca Morelli, F. Remondino, Andrea Micheli, D. Tuia, Benjamin Risse
Abstract. Wildlife research in both terrestrial and aquatic ecosystems now deploys drone technology for tasks such as monitoring, census counts and habitat analysis. Unlike camera traps, drones offer real-time flexibility for adaptable flight paths and camera views, thus making them ideal for capturing multi-view data on wildlife like zebras or lions. With recent advancements in animals’ 3D shape & pose estimation, there is an increasing interest in bringing 3D analysis from ground to sky by means of drones. The paper reports some activities of the EU-funded WildDrone project and performs, for the first time, 3D analyses of animals exploiting oblique drone imagery. Using parametric model fitting, we estimate 3D shape and pose of animals from frames of a monocular RGB video. With the goal of appending metric information to parametric animal models using photogrammetric evidence, we propose a pipeline where we perform a point cloud reconstruction of the scene to scale and localize the animal within the 3D scene. Challenges, planned next steps and future directions are also reported.
{"title":"Towards Estimation of 3D Poses and Shapes of Animals from Oblique Drone Imagery","authors":"Vandita Shukla, Luca Morelli, F. Remondino, Andrea Micheli, D. Tuia, Benjamin Risse","doi":"10.5194/isprs-archives-xlviii-2-2024-379-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-379-2024","url":null,"abstract":"Abstract. Wildlife research in both terrestrial and aquatic ecosystems now deploys drone technology for tasks such as monitoring, census counts and habitat analysis. Unlike camera traps, drones offer real-time flexibility for adaptable flight paths and camera views, thus making them ideal for capturing multi-view data on wildlife like zebras or lions. With recent advancements in animals’ 3D shape & pose estimation, there is an increasing interest in bringing 3D analysis from ground to sky by means of drones. The paper reports some activities of the EU-funded WildDrone project and performs, for the first time, 3D analyses of animals exploiting oblique drone imagery. Using parametric model fitting, we estimate 3D shape and pose of animals from frames of a monocular RGB video. With the goal of appending metric information to parametric animal models using photogrammetric evidence, we propose a pipeline where we perform a point cloud reconstruction of the scene to scale and localize the animal within the 3D scene. Challenges, planned next steps and future directions are also reported.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"95 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141359140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-11DOI: 10.5194/isprs-archives-xlviii-2-2024-241-2024
Scott McAvoy, B. Tanduo, A. Spreafico, F. Chiabrando, D. Rissolo, J. Ristevski, F. Kuester
Abstract. Photogrammetry and LiDAR have become increasingly accessible methods for documentation of Cultural Heritage sites. Academic and government agencies recognize the utility of high-resolution 3D models supporting long-term asset management through visualization, conservation planning, and change detection. Though detailed models can be created with increasing ease, their potential for future use can be constrained by a lack of accompanying topographic data, data collector skill level, and incomplete recording of the key metadata and paradata which make such survey data useful to future endeavors. In this paper, informed by various international survey organizations and data archives, we present a framework to record and communicate Cultural Heritage - focusing on architectures based on 3D metric survey - to first describe the data and metadata which should be included by surveyors to enable data usage and to communicate the expected utility of this data.
{"title":"An Archival Framework for Sharing of Cultural Heritage 3D Survey Data: OpenHeritage3D.org","authors":"Scott McAvoy, B. Tanduo, A. Spreafico, F. Chiabrando, D. Rissolo, J. Ristevski, F. Kuester","doi":"10.5194/isprs-archives-xlviii-2-2024-241-2024","DOIUrl":"https://doi.org/10.5194/isprs-archives-xlviii-2-2024-241-2024","url":null,"abstract":"Abstract. Photogrammetry and LiDAR have become increasingly accessible methods for documentation of Cultural Heritage sites. Academic and government agencies recognize the utility of high-resolution 3D models supporting long-term asset management through visualization, conservation planning, and change detection. Though detailed models can be created with increasing ease, their potential for future use can be constrained by a lack of accompanying topographic data, data collector skill level, and incomplete recording of the key metadata and paradata which make such survey data useful to future endeavors. In this paper, informed by various international survey organizations and data archives, we present a framework to record and communicate Cultural Heritage - focusing on architectures based on 3D metric survey - to first describe the data and metadata which should be included by surveyors to enable data usage and to communicate the expected utility of this data.\u0000","PeriodicalId":505918,"journal":{"name":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"85 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141359787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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