{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:42:32Z","timestamp":1760179352912,"version":"build-2065373602"},"reference-count":78,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,22]],"date-time":"2020-09-22T00:00:00Z","timestamp":1600732800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020","doi-asserted-by":"publisher","award":["740754"],"award-info":[{"award-number":["740754"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The technical progress in the last decades makes photo and video recording devices omnipresent. This change has a significant impact, among others, on police work. It is no longer unusual that a myriad of digital data accumulates after a criminal act, which must be reviewed by criminal investigators to collect evidence or solve the crime. This paper presents the VICTORIA Interactive 4D Scene Reconstruction and Analysis Framework (\u201cISRA-4D\u201d 1.0), an approach for the visual consolidation of heterogeneous video and image data in a 3D reconstruction of the corresponding environment. First, by reconstructing the environment in which the materials were created, a shared spatial context of all available materials is established. Second, all footage is spatially and temporally registered within this 3D reconstruction. Third, a visualization of the hereby created 4D reconstruction (3D scene + time) is provided, which can be analyzed interactively. Additional information on video and image content is also extracted and displayed and can be analyzed with supporting visualizations. The presented approach facilitates the process of filtering, annotating, analyzing, and getting an overview of large amounts of multimedia material. The framework is evaluated using four case studies which demonstrate its broad applicability. Furthermore, the framework allows the user to immerse themselves in the analysis by entering the scenario in virtual reality. This feature is qualitatively evaluated by means of interviews of criminal investigators and outlines potential benefits such as improved spatial understanding and the initiation of new fields of application.<\/jats:p>","DOI":"10.3390\/s20185426","type":"journal-article","created":{"date-parts":[[2020,9,22]],"date-time":"2020-09-22T09:40:56Z","timestamp":1600767656000},"page":"5426","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Toward Mass Video Data Analysis: Interactive and Immersive 4D Scene Reconstruction"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5398-3109","authenticated-orcid":false,"given":"Matthias","family":"Kraus","sequence":"first","affiliation":[{"name":"Department of Computer and Information Science, Universi\u00e4t Konstanz, Universit\u00e4tsstr. 10, 78465 Konstanz, Germany"}]},{"given":"Thomas","family":"Pollok","sequence":"additional","affiliation":[{"name":"Fraunhofer IOSB, Fraunhoferstr. 1, 76131 Karlsruhe, Germany"}]},{"given":"Matthias","family":"Miller","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, Universi\u00e4t Konstanz, Universit\u00e4tsstr. 10, 78465 Konstanz, Germany"}]},{"given":"Timon","family":"Kilian","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, Universi\u00e4t Konstanz, Universit\u00e4tsstr. 10, 78465 Konstanz, Germany"}]},{"given":"Tobias","family":"Moritz","sequence":"additional","affiliation":[{"name":"Fraunhofer IOSB, Fraunhoferstr. 1, 76131 Karlsruhe, Germany"}]},{"given":"Daniel","family":"Schweitzer","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, Universi\u00e4t Konstanz, Universit\u00e4tsstr. 10, 78465 Konstanz, Germany"}]},{"given":"J\u00fcrgen","family":"Beyerer","sequence":"additional","affiliation":[{"name":"Fraunhofer IOSB, Fraunhoferstr. 1, 76131 Karlsruhe, Germany"},{"name":"Vision and Fusion Lab (IES), Karlsruhe Institute of Technology (KIT), c\/o Technologiefabrik, Haid-und-Neu-Str. 7, 76131 Karlsruhe, Germany"}]},{"given":"Daniel","family":"Keim","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, Universi\u00e4t Konstanz, Universit\u00e4tsstr. 10, 78465 Konstanz, Germany"}]},{"given":"Chengchao","family":"Qu","sequence":"additional","affiliation":[{"name":"Fraunhofer IOSB, Fraunhoferstr. 1, 76131 Karlsruhe, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1045-6020","authenticated-orcid":false,"given":"Wolfgang","family":"Jentner","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Science, Universi\u00e4t Konstanz, Universit\u00e4tsstr. 10, 78465 Konstanz, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Qu, C., Metzler, J., and Monari, E. (2018, January 15). ivisX: An Integrated Video Investigation Suite for Forensic Applications. Proceedings of the 2018 IEEE Winter Applications of Computer Vision Workshops (WACVW), Lake Tahoe, NV, USA.","DOI":"10.1109\/WACVW.2018.00007"},{"key":"ref_2","unstructured":"Noack, R. (2020, September 21). Leaked document says 2000 men allegedly assaulted 1200 German women on New Year\u2019s Eve. The Washington Post, Available online: https:\/\/www.washingtonpost.com\/news\/worldviews\/wp\/2016\/07\/10\/leaked-document-says-2000-men-allegedly-assaulted-1200-german-women-on-new-years-eve\/."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pollok, T., Kraus, M., Qu, C., Miller, M., Moritz, T., Kilian, T., Keim, D., and Jentner, W. (2019, January 16\u201318). Computer vision meets visual analytics: Enabling 4D crime scene investigation from image and video data. Proceedings of the 9th International Conference on Imaging for Crime Detection and Prevention (ICDP-2019), London, UK.","DOI":"10.1049\/cp.2019.1166"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/s11263-007-0042-3","article-title":"Vision-Based SLAM: Stereo and Monocular Approaches","volume":"74","author":"Lemaire","year":"2007","journal-title":"Int. J. Comput. Vis."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Sch\u00f6nberger, J.L., and Frahm, J. (2016, January 27\u201330). Structure-from-Motion Revisited. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.445"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zhong, F., Wang, S., Zhang, Z., Chen, C., and Wang, Y. (2018, January 12\u201315). Detect-SLAM: Making Object Detection and SLAM Mutually Beneficial. Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe, NV, USA.","DOI":"10.1109\/WACV.2018.00115"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Bullinger, S., Bodensteiner, C., and Arens, M. (2019, January 27\u201331). 3D Object Trajectory Reconstruction using Stereo Matching and Instance Flow based Multiple Object Tracking. Proceedings of the International Conference on Machine Vision Applications (MVA), Tokyo, Japan.","DOI":"10.23919\/MVA.2019.8757921"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Mustafa, A., Kim, H., Guillemaut, J., and Hilton, A. (2015, January 7\u201313). General Dynamic Scene Reconstruction from Multiple View Video. Proceedings of the IEEE International Conference on Computer Vision (ICCV), Santiago, Chile.","DOI":"10.1109\/ICCV.2015.109"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Ji, D., Dunn, E., and Frahm, J.M. (2016, January 8\u201316). Spatio-Temporally Consistent Correspondence for Dense Dynamic Scene Modeling. Proceedings of the European Conference on Computer Vision (ECCV), Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46466-4_1"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (2016, January 27\u201330). You only look once: Unified, real-time object detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Redmon, J., and Farhadi, A. (2017, January 21\u201326). YOLO9000: Better, faster, stronger. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.690"},{"key":"ref_12","unstructured":"Redmon, J., and Farhadi, A. (2018). YOLOv3: An Incremental Improvement. arXiv."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., and Berg, A.C. (2016, January 8\u201316). Ssd: Single shot multibox detector. Proceedings of the European Conference on Computer Vision (ECCV), Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"ref_14","unstructured":"Dai, J., Li, Y., He, K., and Sun, J. (2016). R-FCN: Object detection via region-based fully convolutional networks. arXiv."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.imavis.2017.07.006","article-title":"Moving object detection and segmentation in urban environments from a moving platform","volume":"68","author":"Zhou","year":"2017","journal-title":"Image Vis. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Huang, Q., Mo, W., Pei, L., and Zeng, L. (2019, January 19\u201321). 3D Coordinate Calculation and Pose Estimation of Power Meter based on Binocular Stereo Vision. Proceedings of the 8th International Conference on Software and Computer Applications (ICSCA\u201919), Penang, Malaysia.","DOI":"10.1145\/3316615.3316655"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Li, X., and Loy, C.C. (2018, January 8\u201314). Video Object Segmentation with Joint Re-identification and Attention-Aware Mask Propagation. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-030-01219-9_6"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Bialkowski, A., Denman, S., Sridharan, S., Fookes, C., and Lucey, P. (2012, January 3\u20135). A database for person re-identification in multi-camera surveillance networks. Proceedings of the 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), Fremantle, Australia.","DOI":"10.1109\/DICTA.2012.6411689"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.imavis.2016.10.010","article-title":"Fully-automated person re-identification in multi-camera surveillance system with a robust kernel descriptor and effective shadow removal method","volume":"59","author":"Pham","year":"2017","journal-title":"Image Vis. Comput."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Yang, T., Chen, F., Kimber, D., and Vaughan, J. (2007, January 2\u20135). Robust people detection and tracking in a multi-camera indoor visual surveillance system. Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, Beijing, China.","DOI":"10.1109\/ICME.2007.4284740"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1109\/TCYB.2014.2350774","article-title":"3-d human action recognition by shape analysis of motion trajectories on riemannian manifold","volume":"45","author":"Devanne","year":"2014","journal-title":"IEEE Trans. Cybern."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s11042-009-0378-5","article-title":"Performance analysis for automated gait extraction and recognition in multi-camera surveillance","volume":"50","author":"Goffredo","year":"2010","journal-title":"Multimed. Tools Appl."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1456","DOI":"10.1109\/5.959341","article-title":"Algorithms for cooperative multisensor surveillance","volume":"89","author":"Collins","year":"2001","journal-title":"Proc. IEEE"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Javed, O., Rasheed, Z., Alatas, O., and Shah, M. (2003, January 6\u20139). KNIGHTM: A real time surveillance system for multiple and non-overlapping cameras. Proceedings of the 2003 International Conference on Multimedia and Expo (ICME\u201903), (Cat. No. 03TH8698), Baltimore, MD, USA.","DOI":"10.1109\/ICME.2003.1221001"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1109\/34.868678","article-title":"Monitoring activities from multiple video streams: Establishing a common coordinate frame","volume":"22","author":"Lee","year":"2000","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_26","unstructured":"Kettnaker, V., and Zabih, R. (1999, January 23\u201325). Bayesian multi-camera surveillance. Proceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (Cat. No PR00149), Fort Collins, CO, USA."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zhao, J., and Sen-ching, S.C. (2007, January 25\u201328). Multi-camera surveillance with visual tagging and generic camera placement. Proceedings of the 2007 First ACM\/IEEE International Conference on Distributed Smart Cameras, Vienna, Austria.","DOI":"10.1109\/ICDSC.2007.4357532"},{"key":"ref_28","unstructured":"Lim, S.N., Elgammal, A., and Davis, L.S. (2003, January 6\u20139). Image-based pan-tilt camera control in a multi-camera surveillance environment. Proceedings of the 2003 International Conference on Multimedia and Expo (ICME\u201903), (Cat. No. 03TH8698), Baltimore, MD, USA."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Shen, C., Zhang, C., and Fels, S. (2007, January 16\u201319). A multi-camera surveillance system that estimates quality-of-view measurement. Proceedings of the 2007 IEEE International Conference on Image Processing, San Antonio, TX, USA.","DOI":"10.1109\/ICIP.2007.4379279"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Keim, D., Andrienko, G., Fekete, J.D., G\u00f6rg, C., Kohlhammer, J., and Melan\u00e7on, G. (2008). Visual analytics: Definition, process, and challenges. Information Visualization, Springer.","DOI":"10.1007\/978-3-540-70956-5_7"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/MCG.2004.39","article-title":"Visual analytics","volume":"5","author":"Wong","year":"2004","journal-title":"IEEE Comput. Graph. Appl."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Keim, D.A., Mansmann, F., Schneidewind, J., Thomas, J., and Ziegler, H. (2008). Visual analytics: Scope and challenges. Visual Data Mining, Springer.","DOI":"10.1007\/978-3-540-71080-6_6"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1604","DOI":"10.1109\/TVCG.2014.2346481","article-title":"Knowledge generation model for visual analytics","volume":"20","author":"Sacha","year":"2014","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1863","DOI":"10.1109\/TVCG.2014.2346926","article-title":"Proactive spatiotemporal resource allocation and predictive visual analytics for community policing and law enforcement","volume":"20","author":"Malik","year":"2014","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1080\/07418825.2012.673632","article-title":"The effects of hot spots policing on crime: An updated systematic review and meta-analysis","volume":"31","author":"Braga","year":"2014","journal-title":"Justice Q."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Sathiyanarayanan, M., Junejo, A.K., and Fadahunsi, O. (2019, January 12\u201314). Visual Analysis of Predictive Policing to Improve Crime Investigation. Proceedings of the 2019 International Conference on contemporary Computing and Informatics (IC3I), Singapore.","DOI":"10.1109\/IC3I46837.2019.9055515"},{"key":"ref_37","unstructured":"Sacha, D., Jentner, W., Zhang, L., Stoffel, F., Ellis, G., and Keim, D. (2017). Applying Visual Interactive Dimensionality Reduction to Criminal Intelligence Analysis. VALCRI White Paper Series, VALCRI."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1007\/s00371-018-1483-0","article-title":"Making machine intelligence less scary for criminal analysts: Reflections on designing a visual comparative case analysis tool","volume":"34","author":"Jentner","year":"2018","journal-title":"Vis. Comput."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1162\/pres.1992.1.3.344","article-title":"A literature survey for virtual environments: Military flight simulator visual systems and simulator sickness","volume":"1","author":"Pausch","year":"1992","journal-title":"Presence Teleoperators Virtual Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.compedu.2013.07.033","article-title":"Effectiveness of virtual reality-based instruction on students\u2019 learning outcomes in K-12 and higher education: A meta-analysis","volume":"70","author":"Merchant","year":"2014","journal-title":"Comput. Educ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"S91","DOI":"10.1097\/00042871-200701010-00099","article-title":"The Impact of the Degree of Immersion Upon Learning Performance in Virtual Reality Simulations for Medical Education","volume":"55","author":"Pierce","year":"2007","journal-title":"J. Investig. Med."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Marriott, K., Schreiber, F., Dwyer, T., Klein, K., Riche, N.H., Itoh, T., Stuerzlinger, W., and Thomas, B.H. (2018). Immersive Analytics, Springer.","DOI":"10.1007\/978-3-030-01388-2"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1731","DOI":"10.1021\/acs.jcim.8b00402","article-title":"Exploring drugbank in virtual reality chemical space","volume":"58","author":"Probst","year":"2018","journal-title":"J. Chem. Inf. Model."},{"key":"ref_44","unstructured":"Zhang, S., Demiralp, C., Keefe, D.F., DaSilva, M., Laidlaw, D.H., Greenberg, B.D., Basser, P.J., Pierpaoli, C., Chiocca, E.A., and Deisboeck, T.S. (2001, January 21\u201326). An immersive virtual environment for DT-MRI volume visualization applications: A case study. Proceedings of the Visualization (VIS\u201901), San Diego, CA, USA."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Donalek, C., Djorgovski, S.G., Cioc, A., Wang, A., Zhang, J., Lawler, E., Yeh, S., Mahabal, A., Graham, M., and Drake, A. (2014, January 27\u201330). Immersive and collaborative data visualization using virtual reality platforms. Proceedings of the 2014 IEEE International Conference on Big Data (BigData), Washington DC, USA.","DOI":"10.1109\/BigData.2014.7004282"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Kraus, M., Weiler, N., Breitkreutz, T., Keim, D.A., and Stein, M. (2019, January 25\u201327). Breaking the curse of visual data exploration: Improving analyses by building bridges between data world and real world. Proceedings of the 10th International Conference on Information Visualization Theory and Applications (IVAPP), Prague, Czech Republic.","DOI":"10.5220\/0007257400002108"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1109\/TVCG.2019.2934395","article-title":"The impact of immersion on cluster identification tasks","volume":"26","author":"Kraus","year":"2019","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Kraus, M., Angerbauer, K., Buchm\u00fcller, J., Schweitzer, D., Keim, D.A., Sedlmair, M., and Fuchs, J. (2020, January 25\u201330). Assessing 2D and 3D Heatmaps for Comparative Analysis: An Empirical Study. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA.","DOI":"10.1145\/3313831.3376675"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Merino, L., Fuchs, J., Blumenschein, M., Anslow, C., Ghafari, M., Nierstrasz, O., Behrisch, M., and Keim, D.A. (2017, January 18\u201319). On the Impact of the Medium in the Effectiveness of 3D Software Visualizations. Proceedings of the 2017 IEEE Working Conference on Software Visualization (VISSOFT), Shangahi, China.","DOI":"10.1109\/VISSOFT.2017.17"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Etemadpour, R., Monson, E., and Linsen, L. (2013, January 16\u201318). The effect of stereoscopic immersive environments on projection-based multi-dimensional data visualization. Proceedings of the 2013 17th International Conference on Information Visualisation, London, UK.","DOI":"10.1109\/IV.2013.51"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., and Girshick, R.B. (2017). Mask R-CNN. arXiv.","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Lin, T., Maire, M., Belongie, S.J., Bourdev, L.D., Girshick, R.B., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., and Zitnick, C.L. (2014). Microsoft COCO: Common Objects in Context. arXiv.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Triggs, B., McLauchlan, P., Hartley, R., and Fitzgibbon, A. (2000). Bundle Adjustment\u2014A Modern Synthesis. International Workshop on Vision Algorithms, Springer.","DOI":"10.1007\/3-540-44480-7_21"},{"key":"ref_54","unstructured":"Cernea, D. (2020, September 19). OpenMVS: Multi-View Stereo Reconstruction Library. Available online: https:\/\/cdcseacave.github.io\/openMVS."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Konolige, K. (1997). Small vision system: Hardware and implementation. Robotics Research, Springer.","DOI":"10.1007\/978-1-4471-1580-9_19"},{"key":"ref_56","unstructured":"Hirschmuller, H. (2005, January 20\u201325). Accurate and efficient stereo processing by semi-global matching and mutual information. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201905), San Diego, CA, USA."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Godard, C., Aodha, O.M., and Brostow, G.J. (2018). Digging Into Self-Supervised Monocular Depth Estimation. arXiv.","DOI":"10.1109\/ICCV.2019.00393"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Tosi, F., Aleotti, F., Poggi, M., and Mattoccia, S. (2019, January 16\u201320). Learning monocular depth estimation infusing traditional stereo knowledge. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.01003"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Hermann, M., Ruf, B., Weinmann, M., and Hinz, S. (2020). Self-Supervised Learning for Monocular Depth Estimation from Aerial Imagery. arXiv.","DOI":"10.5194\/isprs-annals-V-2-2020-357-2020"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., and Urtasun, R. (2012, January 16\u201321). Are we ready for autonomous driving? The KITTI vision benchmark suite. Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, USA.","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Li, Z., Dekel, T., Cole, F., Tucker, R., Snavely, N., Liu, C., and Freeman, W.T. (2019). Learning the Depths of Moving People by Watching Frozen People. arXiv.","DOI":"10.1109\/CVPR.2019.00465"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Guizilini, V., Ambrus, R., Pillai, S., and Gaidon, A. (2019). PackNet-SfM: 3D Packing for Self-Supervised Monocular Depth Estimation. arXiv.","DOI":"10.1109\/CVPR42600.2020.00256"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Cao, Z., Hidalgo, G., Simon, T., Wei, S., and Sheikh, Y. (2018). OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields. arXiv.","DOI":"10.1109\/CVPR.2017.143"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Saito, S., Simon, T., Saragih, J., and Joo, H. (2020, January 14\u201319). PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Online.","DOI":"10.1109\/CVPR42600.2020.00016"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Saito, S., Huang, Z., Natsume, R., Morishima, S., Kanazawa, A., and Li, H. (2019). PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization. arXiv.","DOI":"10.1109\/ICCV.2019.00239"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Wang, T., Hu, X., Wang, Q., Heng, P.A., and Fu, C.W. (2020, January 14\u201319). Instance Shadow Detection. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Online.","DOI":"10.1109\/CVPR42600.2020.00195"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cviu.2016.09.002","article-title":"3D Human pose estimation: A review of the literature and analysis of covariates","volume":"152","author":"Sarafianos","year":"2016","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Pollok, T. (2018, January 29\u201331). A New Multi-Camera Dataset with Surveillance, Mobile and Stereo Cameras for Tracking, Situation Analysis and Crime Scene Investigation Applications. Proceedings of the 2018 the 2nd International Conference on Video and Image Processing (ICVIP 2018), Hong Kong, China.","DOI":"10.1145\/3301506.3301542"},{"key":"ref_69","unstructured":"(2020, July 30). Valve Index Developer Website. Available online: https:\/\/store.steampowered.com\/valveindex\/."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1162\/105474699566143","article-title":"Navigating large-scale virtual environments: What differences occur between helmet-mounted and desk-top displays?","volume":"8","author":"Ruddle","year":"1999","journal-title":"Presence Teleoperators Virtual Environ."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Riecke, B.E., and Schulte-Pelkum, J. (2013). Perceptual and cognitive factors for self-motion simulation in virtual environments: How can self-motion illusions (\u201cvection\u201d) be utilized?. Human Walking in Virtual Environments, Springer.","DOI":"10.1007\/978-1-4419-8432-6_2"},{"key":"ref_72","unstructured":"Naudts, L., and Vogiatzoglou, P. (2020, August 19). The VICTORIA Ethical and Legal Management Toolkit: Practice and Theory for Video Surveillance. Available online: https:\/\/lirias.kuleuven.be\/2954812?limo=0."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Oneto, L., and Chiappa, S. (2020). Fairness in Machine Learning. Recent Trends in Learning From Data, Springer.","DOI":"10.1007\/978-3-030-43883-8"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Rademacher, T. (2020). Artificial intelligence and law enforcement. Regulating Artificial Intelligence, Springer.","DOI":"10.1007\/978-3-030-32361-5_10"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Naudts, L. (2019). Criminal Profiling and Non-Discrimination: On Firm Grounds for the Digital Era?. Security and Law. Legal and Ethical Aspects of Public Security, Cyber Security and Critical Infrastructure Security, Intersentia.","DOI":"10.1017\/9781780688909.004"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1016\/j.clsr.2017.11.004","article-title":"Having yes, using no? About the new legal regime for biometric data","volume":"34","author":"Kindt","year":"2018","journal-title":"Comput. Law Secur. Rev."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Clark, H.H., and Brennan, S.E. (1991). Grounding in communication. Perspectives on Socially Shared Cognition, American Psychological Association.","DOI":"10.1037\/10096-006"},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"M\u00fcller, J., Butscher, S., Feyer, S.P., and Reiterer, H. (2017, January 26\u201329). Studying collaborative object positioning in distributed augmented realities. Proceedings of the 16th International Conference on Mobile and Ubiquitous Multimedia, Stuttgart, Germany.","DOI":"10.1145\/3152832.3152856"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/18\/5426\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:12:21Z","timestamp":1760177541000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/18\/5426"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,22]]},"references-count":78,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["s20185426"],"URL":"https:\/\/doi.org\/10.3390\/s20185426","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2020,9,22]]}}}