{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T23:14:43Z","timestamp":1784243683048,"version":"3.55.0"},"reference-count":36,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,14]],"date-time":"2020-11-14T00:00:00Z","timestamp":1605312000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072053"],"award-info":[{"award-number":["62072053"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The Fundamental Research Funds for the Central Universities","award":["300102249317"],"award-info":[{"award-number":["300102249317"]}]},{"DOI":"10.13039\/501100007128","name":"Natural Science Foundation of Shaanxi Province","doi-asserted-by":"publisher","award":["2019SF-258"],"award-info":[{"award-number":["2019SF-258"]}],"id":[{"id":"10.13039\/501100007128","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R &amp; D Program of China","award":["2019YFB1600500"],"award-info":[{"award-number":["2019YFB1600500"]}]},{"name":"Key R &amp; D project of Shaanxi Science and Technology Department","award":["2019YFB1600500"],"award-info":[{"award-number":["2019YFB1600500"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The three-dimensional trajectory data of vehicles have important practical meaning for traffic behavior analysis. To solve the problems of narrow visual angle in single-camera scenes and lack of continuous trajectories in 3D space by current cross-camera trajectory extraction methods, we propose an algorithm of vehicle spatial distribution and 3D trajectory extraction in this paper. First, a panoramic image of a road with spatial information is generated based on camera calibration, which is used to convert cross-camera perspectives into 3D physical space. Then, we choose YOLOv4 to obtain 2D bounding boxes of vehicles in cross-camera scenes. Based on the above information, 3D bounding boxes around vehicles are built with geometric constraints which are used to obtain projection centroids of vehicles. Finally, by calculating the spatial distribution of projection centroids in the panoramic image, 3D trajectories of vehicles are extracted. The experimental results indicate that our algorithm can effectively complete vehicle spatial distribution and 3D trajectory extraction in various traffic scenes, which outperforms other comparison algorithms.<\/jats:p>","DOI":"10.3390\/s20226517","type":"journal-article","created":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T21:48:52Z","timestamp":1605563332000},"page":"6517","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Vehicle Spatial Distribution and 3D Trajectory Extraction Algorithm in a Cross-Camera Traffic Scene"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2553-3623","authenticated-orcid":false,"given":"Xinyao","family":"Tang","sequence":"first","affiliation":[{"name":"School of Information Engineering, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huansheng","family":"Song","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanni","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1773","DOI":"10.1109\/TITS.2013.2266661","article-title":"Looking at Vehicles on the Road: A Survey of Vision-Based Vehicle Detection, Tracking, and Behavior Analysis","volume":"14","author":"Sivaraman","year":"2013","journal-title":"IEEE Trans. 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