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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pham, V.-Q. Kozakaya, T. Okada, R. |
| Copyright Year | 2014 |
| Description | Author affiliation: Corp. R&D Center, Toshiba Corp., Kawasaki, Japan (Pham, V.-Q.; Kozakaya, T.; Okada, R.) |
| Abstract | While online approaches for multi-person tracking are still hard to deal with occlusions, many tracking methods use a global data association approach to find person trajectories on a long segment of consecutive frames. Such offline approaches often cause long output latencies, which are unsuitable for camera-based surveillance systems. Based on an observation that the current position of an object should be estimated from both its past and future positions that are observed in a short period of time, we propose a novel object tracking method based on a dynamic programming framework. This method iteratively associates and integrates track lets obtained by visual tracking which are observed just before and after occlusions. We always produce outputs at a constant short delay time, and requires only the standard HOG detector for high performance. Our tracking method can run at 10-60 fps on a single CPU core, and attains the state-of-the-art performance for the Town Center dataset. |
| Starting Page | 1206 |
| Ending Page | 1211 |
| File Size | 706384 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479952090 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2014.217 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-24 |
| Publisher Place | Sweden |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Detectors Target tracking Visualization Interpolation Cities and towns Feature extraction Object tracking |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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