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Recovering people tracking errors using enhanced covariance-based signatures
Abstract : This paper presents a new approach for tracking multiple persons in a single camera. This approach focuses on re- covering tracked individuals that have been lost and are detected again, after being miss-detected (e.g. occluded) or after leaving the scene and coming back. In order to correct tracking errors, a multi-cameras re-identification method is adapted, with a real-time constraint. The proposed ap- proach uses a highly discriminative human signature based on covariance matrix, improved using background subtrac- tion, and a people detection confidence. The problem of linking several tracklets belonging to the same individual is also handled as a ranking problem using a learned pa- rameter. The objective is to create clusters of tracklets de- scribing the same individual. The evaluation is performed on PETS2009 dataset showing promising results.
Cited literature [13 references]
https://hal.inria.fr/hal-00761322
Contributor : Julien Badie <>
Submitted on : Wednesday, December 5, 2012 - 11:56:46 AM
Last modification on : Thursday, March 5, 2020 - 5:34:22 PM
Long-term archiving on: : Wednesday, March 6, 2013 - 5:45:09 AM
Contributor : Julien Badie <>
Submitted on : Wednesday, December 5, 2012 - 11:56:46 AM
Last modification on : Thursday, March 5, 2020 - 5:34:22 PM
Long-term archiving on: : Wednesday, March 6, 2013 - 5:45:09 AM
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