{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T20:11:52Z","timestamp":1783973512260,"version":"3.55.0"},"reference-count":40,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,2,2]],"date-time":"2022-02-02T00:00:00Z","timestamp":1643760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"university research team development fund","award":["f4211"],"award-info":[{"award-number":["f4211"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Surveillance systems focus on the image itself, mainly from the perspective of computer vision, which lacks integration with geographic information. It is difficult to obtain the location, size, and other spatial information of moving objects from surveillance systems, which lack any ability to couple with the geographical environment. To overcome such limitations, we propose a fusion framework of 3D geographic information and moving objects in surveillance video, which provides ideas for related research. We propose a general framework that can extract objects\u2019 spatial\u2013temporal information and visualize object trajectories in a 3D model. The framework does not rely on specific algorithms for determining the camera model, object extraction, or the mapping model. In our experiment, we used the Zhang Zhengyou calibration method and the EPNP method to determine the camera model, YOLOv5 and deep SORT to extract objects from a video, and an imaging ray intersection with the digital surface model to locate objects in the 3D geographical scene. The experimental results show that when the bounding box can thoroughly outline the entire object, the maximum error and root mean square error of the planar position are within 31 cm and 10 cm, respectively, and within 10 cm and 3 cm, respectively, in elevation. The errors of the average width and height of moving objects are within 5 cm and 2 cm, respectively, which is consistent with reality. To our knowledge, we first proposed the general fusion framework. This paper offers a solution to integrate 3D geographic information and surveillance video, which will not only provide a spatial perspective for intelligent video analysis, but also provide a new approach for the multi-dimensional expression of geographic information, object statistics, and object measurement.<\/jats:p>","DOI":"10.3390\/ijgi11020103","type":"journal-article","created":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T05:42:33Z","timestamp":1643866953000},"page":"103","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Extracting Objects\u2019 Spatial\u2013Temporal Information Based on Surveillance Videos and the Digital Surface Model"],"prefix":"10.3390","volume":"11","author":[{"given":"Shijing","family":"Han","sequence":"first","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"},{"name":"School of Natural Resources and Surveying, Nanning Normal University, Nanning 530001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7319-7260","authenticated-orcid":false,"given":"Xiaorui","family":"Dong","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyang","family":"Hao","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shufeng","family":"Miao","sequence":"additional","affiliation":[{"name":"Wuhan Kedao Geographical Information Engineering Co., Ltd., Wuhan 430081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103116","DOI":"10.1016\/j.jvcir.2021.103116","article-title":"A review of video surveillance systems","volume":"77","author":"Elharrouss","year":"2021","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Lee, S.C., and Nevatia, R. (2011, January 20\u201325). Robust camera calibration tool for video surveillance camera in urban environment. Proceedings of the CVPR 2011 Workshops, Colorado Springs, CO, USA.","DOI":"10.1109\/CVPRW.2011.5981777"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1016\/j.ijinfomgt.2019.04.017","article-title":"PTZ-surveillance coverage based on artificial intelligence for smart cities","volume":"49","author":"Eldrandaly","year":"2019","journal-title":"Int. J. Inf. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1895","DOI":"10.1007\/s40747-020-00161-4","article-title":"Overview and methods of correlation filter algorithms in object tracking","volume":"7","author":"Liu","year":"2020","journal-title":"Complex Intell. Syst."},{"key":"ref_5","unstructured":"Kawasaki, N., and Takai, Y. (2002, January 4\u20136). Video monitoring system for security surveillance based on augmented reality. Proceedings of the 12th International Conference on Artificial Reality and Telexistence, Tokyo, Japan."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sankaranarayanan, K., and Davis, J.W. (2008, January 1\u20133). A fast linear registration framework for multi-camera GIS coordination. Proceedings of the 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance, Santa Fe, NM, USA.","DOI":"10.1109\/AVSS.2008.20"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Xie, Y., Wang, M., Liu, X., Mao, B., and Wang, F. (2019). Integration of Multi-Camera Video Moving Objects and GIS. ISPRS Int. J. Geo. Inf., 8.","DOI":"10.3390\/ijgi8120561"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Xie, Y., Wang, M., Liu, X., and Wu, Y. (2017). Integration of GIS and moving objects in surveillance video. ISPRS Int. J. Geo. Inf., 6.","DOI":"10.3390\/ijgi6040094"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Girgensohn, A., Kimber, D., Vaughan, J., Yang, T., Shipman, F., Turner, T., Rieffel, E., Wilcox, L., Chen, F., and Dunnigan, T. (2007, January 24\u201329). Dots: Support for effective video surveillance. Proceedings of the 15th ACM international conference on Multimedia, Bavaria, Germany.","DOI":"10.1145\/1291233.1291332"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Han, L., Huang, B., and Chen, L. (2010, January 18\u201320). Integration and application of video surveillance system and 3DGIS. Proceedings of the 2010 18th International Conference on Geoinformatics, Beijing, China.","DOI":"10.1109\/GEOINFORMATICS.2010.5568152"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"022088","DOI":"10.1088\/1755-1315\/170\/2\/022088","article-title":"An integrated system of video surveillance and GIS","volume":"170","author":"Zheng","year":"2018","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Xie, Y., Wang, M., Liu, X., and Wu, Y. (2017). Surveillance Video Synopsis in GIS. ISPRS Int. J. Geo Inf., 6.","DOI":"10.3390\/ijgi6110333"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Song, H., Liu, X., Zhang, X., and Hu, J. (2012, January 1\u20133). Real-time monitoring for crowd counting using video surveillance and GIS. Proceedings of the 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, Nanjing, China.","DOI":"10.1109\/RSETE.2012.6260673"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1109\/34.888718","article-title":"A flexible new technique for camera calibration","volume":"22","author":"Zhang","year":"2000","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1007957826135","article-title":"Self-calibration of stationary cameras","volume":"22","author":"Hartley","year":"1997","journal-title":"Int. J. Comput. Vis."},{"key":"ref_16","unstructured":"Triggs, B. (1997, January 17\u201319). Autocalibration and the absolute quadric. Proceedings of the Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, PR, USA."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"052009","DOI":"10.1088\/1742-6596\/1087\/5\/052009","article-title":"A review of solutions for perspective-n-point problem in camera pose estimation","volume":"1087","author":"Lu","year":"2018","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s11263-008-0152-6","article-title":"Epnp: An accurate o (n) solution to the pnp problem","volume":"81","author":"Lepetit","year":"2009","journal-title":"Int. J. Comput. Vis."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.1109\/TPAMI.2012.41","article-title":"A robust O (n) solution to the perspective-n-point problem","volume":"34","author":"Li","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_20","unstructured":"Collins, R., Tsin, Y., Miller, J.R., and Lipton, A. (1998, January 20\u201323). Using a DEM to determine geospatial object trajectories. Proceedings of the DARPA Image Understanding Workshop, Monterey, CA, USA."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Milosavljevi\u0107, A., Ran\u010di\u0107, D., Dimitrijevi\u0107, A., Predi\u0107, B., and Mihajlovi\u0107, V. (2016). Integration of GIS and video surveillance. Int. J. Geogr. Inf. Sci., 1\u201319.","DOI":"10.1080\/13658816.2016.1161197"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Milosavljevi\u0107, A., Ran\u010di\u0107, D., Dimitrijevi\u0107, A., Predi\u0107, B., and Mihajlovi\u0107, V. (2017). A Method for Estimating Surveillance Video Georeferences. ISPRS Int. J. Geo. Inf., 6.","DOI":"10.3390\/ijgi6070211"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., and Malik, J. (2014, January 23\u201328). Rich feature hierarchies for accurate object detection and semantic segmentation. Proceedings of the Proceedings of the IEEE conference on computer vision and pattern recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Girshick, R. (2015, January 7\u201313). Fast r-cnn. Proceedings of the Proceedings of the IEEE international conference on computer vision, Santiago, Chile.","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref_25","first-page":"91","article-title":"Faster r-cnn: Towards real-time object detection with region proposal networks","volume":"28","author":"Ren","year":"2015","journal-title":"Adv. Neural Inf. Processing Syst."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., and Girshick, R. (2017, January 22\u201329). Mask r-cnn. Proceedings of the Proceedings of the IEEE international Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref_27","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 Proceedings of the IEEE conference on computer vision and pattern recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., and Berg, A.C. (2016, January 11\u201314). Ssd: Single shot multibox detector. Proceedings of the European Conference on Computer Vision, Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1109\/TPAMI.2012.159","article-title":"Multiple target tracking by learning-based hierarchical association of detection responses","volume":"35","author":"Huang","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5191","DOI":"10.1109\/TIP.2020.2980070","article-title":"Multi-target multi-camera tracking by tracklet-to-target assignment","volume":"29","author":"He","year":"2020","journal-title":"IEEE Trans. Image Processing"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"107153","DOI":"10.1016\/j.compeleceng.2021.107153","article-title":"A novel multi-target multi-camera tracking approach based on feature grouping","volume":"92","author":"Xu","year":"2021","journal-title":"Comput. Electr. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zheng, L., Liu, Y., Li, Y., and Wang, S. (2020, January 23\u201328). Towards real-time multi-object tracking. Proceedings of the Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK.","DOI":"10.1007\/978-3-030-58621-8_7"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Ristani, E., and Tomasi, C. (2018, January 18\u201323). Features for multi-target multi-camera tracking and re-identification. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00632"},{"key":"ref_34","unstructured":"Zhang, Z., Wu, J., Zhang, X., and Zhang, C. (2017). Multi-target, multi-camera tracking by hierarchical clustering: Recent progress on dukemtmc project. arXiv."},{"key":"ref_35","unstructured":"Tagore, N.K., Singh, A., Manche, S., and Chattopadhyay, P. (2020). Deep Learning based Person Re-identification. arXiv."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/s005300050043","article-title":"Towards video-based immersive environments","volume":"5","author":"Katkere","year":"1997","journal-title":"Multimed. Syst."},{"key":"ref_37","first-page":"663","article-title":"Digital diorama: Sensing-based real-world visualization","volume":"Volume II","author":"Takehara","year":"2010","journal-title":"Proceedings of the International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Zhang, X., Liu, X., and Song, H. (2013, January 20\u201322). Video surveillance GIS: A novel application. Proceedings of the 2013 21st International Conference on Geoinformatics, Kaifeng, China.","DOI":"10.1109\/Geoinformatics.2013.6626079"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Yang, Y., Chang, M.-C., Tu, P., and Lyu, S. (2015, January 27\u201330). Seeing as it happens: Real time 3D video event visualization. Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP), Quebec, ON, Canada.","DOI":"10.1109\/ICIP.2015.7351328"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A., and Paulus, D. (2017, January 17\u201320). Simple online and realtime tracking with a deep association metric. Proceedings of the 2017 IEEE International Conference on Image Processing (ICIP), Beijing, China.","DOI":"10.1109\/ICIP.2017.8296962"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/2\/103\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:12:54Z","timestamp":1760134374000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/2\/103"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,2]]},"references-count":40,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["ijgi11020103"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11020103","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,2]]}}}