{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/ocmctrack-online-multi-target-multi-camera","title":"OCMCTrack: Online Multi-Target Multi-Camera Tracking with Corrective Matching Cascade","arxiv_id":null,"date":"2024-06-17","proceeding":"CVPR 2024 6","authors":["Andreas Specker"],"abstract":"The implementation of multi-target multi-camera tracking systems in indoor environments including shops and warehouses facilitates strategic product positioning and the improvement of operational workflows. This paper presents the online multi-target multi-camera tracking framework OCMCTrack which tracks the 3D positions of people in the world. The proposed framework introduces a novel matching cascade to re-evaluate track assignments dynamically thus minimizing false positive associations often made by online trackers. Additionally this work presents three effective methods to enhance the transformation of a person's position in the image to world coordinates thereby addressing common inaccuracies in positional reference points. The proposed methodology is able to achieve competitive performance in Track 1 of the 2024 AI City Challenge demonstrating the effectiveness of the framework.","url_abs":"https://openaccess.thecvf.com/content/CVPR2024W/AICity/html/Specker_OCMCTrack_Online_Multi-Target_Multi-Camera_Tracking_with_Corrective_Matching_Cascade_CVPRW_2024_paper.html","url_pdf":"https://openaccess.thecvf.com/content/CVPR2024W/AICity/papers/Specker_OCMCTrack_Online_Multi-Target_Multi-Camera_Tracking_with_Corrective_Matching_Cascade_CVPRW_2024_paper.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"multi-object-tracking","task_name":"Multi-Object Tracking"},{"task_slug":null,"task_name":"Position"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/multi-object-tracking-on-2024-ai-city","task":"Multi-Object Tracking","dataset":"2024 AI City Challenge","model":"FraunhoferIOSB","rank_in_archive_order":5,"of":8,"metrics":{"AssA":"55.20","DetA":"69.54","HOTA":"60.88","LocA":"87.97"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}