Tracking Multiple People under Global Appearance Constraints

In this paper, we show that tracking multiple people whose paths may intersect can be formulated as a convex global optimization problem. Our proposed framework is designed to exploit image appearance cues to prevent identity switches. Our method is effective even when such cues are only available at distant time intervals. This is unlike many current approaches that depend on appearance being exploitable from frame to frame. We validate our approach on three multi-camera sport and pedestrian datasets that contain long and complex sequences. Our algorithm perseveres identities better than state-of-the-art algorithms while keeping similar MOTA scores.


Published in:
2011 Ieee International Conference On Computer Vision (Iccv), 137-144
Presented at:
International Conference on Computer Vision, Barcelona, Spain, November 6-13, 2011
Year:
2011
Publisher:
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa
ISBN:
978-1-4577-1102-2
Keywords:
Laboratories:




 Record created 2011-08-11, last modified 2018-03-17

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