Automatic Tracker Selection w.r.t Object Detection PerformanceReport as inadecuate




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1 STARS - Spatio-Temporal Activity Recognition Systems CRISAM - Inria Sophia Antipolis - Méditerranée

Abstract : The tracking algorithm performance depends on video content. This paper presents a new multi-object tracking approach which is able to cope with video content variations. First the object detection is improved using Kanade- Lucas-Tomasi KLT feature tracking. Second, for each mobile object, an appropriate tracker is selected among a KLT-based tracker and a discriminative appearance-based tracker. This selection is supported by an online tracking evaluation. The approach has been experimented on three public video datasets. The experimental results show a better performance of the proposed approach compared to recent state of the art trackers.

Keywords : object tracking tracker selection discriminative method KLT online tracking evaluation





Author: Duc Phu Chau - François Bremond - Monique Thonnat - Slawomir Bak -

Source: https://hal.archives-ouvertes.fr/



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