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Représenter pour suivre : exploitation de représentations parcimonieuses pour le suivi multi-objets

Loïc Pierre Fagot-Bouquet 1
1 LAAS-RAP - Équipe Robotique, Action et Perception
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : Despite recent advances in object detection, multi-object tracking still raises some specific issues and therefore remains a challenging problem. In this thesis, we propose to investigate the use of sparse representations within multi-object tracking approaches in order to gain in performances. The first contribution of this thesis consists in designing an online tracking approach that takes advantage of collaborative sparse representations to better distinguish between the targets. Then, structured sparse representations are considered in order to be more suited to traking approaches based on a sliding window. In order to rely less on the object detector quality, we consider for the last contribution of this thesis to use dense dictionaries that are taking into account a large number of undetected locations inside each frame.
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  • HAL Id : tel-01516921, version 2

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Loïc Pierre Fagot-Bouquet. Représenter pour suivre : exploitation de représentations parcimonieuses pour le suivi multi-objets. Automatique. Université Paul Sabatier - Toulouse III, 2017. Français. ⟨NNT : 2017TOU30030⟩. ⟨tel-01516921v2⟩

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