Papers › An Online Approach and Evaluation Method for Tracking People Across Cameras in...
An Online Approach and Evaluation Method for Tracking People Across Cameras in Extremely Long Video Sequence
Cheng-Yen Yang, Hsiang-Wei Huang, Pyong-Kun Kim, Zhongyu Jiang, Kwang-Ju Kim, Chung-I Huang, Haiqing Du, Jenq-Neng Hwang
Multi-camera Multi-Object Tracking has drawn significant attention in recent years due to its critical role in surveillance analytics and related fields. Various challenges including non-overlapping regions varying occlusion conditions and the need for cross-domain generalization in multi-camera tracking systems remain unsolved in the field. We propose a novel online tracking framework that capitalizes on real-time camera calibration to achieve consistent multi-object tracking across camera networks. Our approach seamlessly integrates spatial and temporal association techniques ensuring robust tracking even in long-duration videos. However standard tracking evaluation metrics like CLEAR or HOTA fall short of accurately interpreting the performance of tracking over extended video sequences. Another contribution of this study is the proposal of a new evaluation metric mHOTA which provides a better assessment of tracking performance over prolonged periods. Our comprehensive experiments on the AIC24 Multi-Camera People Tracking dataset demonstrate the effectiveness and scalability of our method along with the capability of the proposed evaluation metric.
Code
No code repository is listed for this paper in the archive or in Syntology's graph.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Multi-Object Tracking | 2024 AI City Challenge | UW-ETRI | AssA | 54.80 | #6 of 8 | Archive leaderboard | report |
| Multi-Object Tracking | 2024 AI City Challenge | UW-ETRI | DetA | 59.88 | #6 of 8 | Archive leaderboard | report |
| Multi-Object Tracking | 2024 AI City Challenge | UW-ETRI | HOTA | 57.14 | #6 of 8 | Archive leaderboard | report |
| Multi-Object Tracking | 2024 AI City Challenge | UW-ETRI | LocA | 91.24 | #6 of 8 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections