Optimizing process for tracking people in video-camera network

Julien Badie 1
1 STARS - Spatio-Temporal Activity Recognition Systems
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : This thesis addresses the problem of improving the performance of people tracking process in a new framework called Global Tracker, which evaluates the quality of people trajectory (obtained by simple tracker) and recovers the potential errors from the previous stage. The first part of this Global Tracker estimates the quality of the tracking results, based on a statistical model analyzing the distribution of the target features to detect potential anomalies.To differentiate real errors from natural phenomena, we analyze all the interactions between the tracked object and its surroundings (other objects and background elements). In the second part, a post tracking method is designed to associate different tracklets (segments of trajectory) corresponding to the same person which were not associated by a first stage of tracking. This tracklet matching process selects the most relevant appearance features to compute a visual signature for each tracklet. Finally, the Global Tracker is evaluated with various benchmark datasets reproducing real-life situations, outperforming the state-of-the-art trackers.
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Theses
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https://hal.inria.fr/tel-01254613
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Julien Badie. Optimizing process for tracking people in video-camera network. Other [cs.OH]. Université Nice Sophia Antipolis, 2015. English. ⟨NNT : 2015NICE4090⟩. ⟨tel-01254613v2⟩

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