On Pairwise Cost for Multi-Object Network Flow Tracking

Visesh Chari 1, 2 Simon Lacoste-Julien 2, 3, 4 Ivan Laptev 2, 1 Josef Sivic 2, 1
1 WILLOW - Models of visual object recognition and scene understanding
CNRS - Centre National de la Recherche Scientifique : UMR8548, Inria Paris-Rocquencourt, DI-ENS - Département d'informatique de l'École normale supérieure
3 SIERRA - Statistical Machine Learning and Parsimony
DI-ENS - Département d'informatique de l'École normale supérieure, ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : Multi-object tracking has been recently approached with the min-cost network flow optimization techniques. Such methods simultaneously resolve multiple object tracks in a video and enable modeling of dependencies among tracks. Min-cost network flow methods also fit well within the "tracking-by-detection" paradigm where object trajectories are obtained by connecting per-frame outputs of an object detector. Object detectors, however, often fail due to occlusions and clutter in the video. To cope with such situations, we propose to add pairwise costs to the min-cost network flow framework. While integer solutions to such a problem become NP-hard, we design a convex relaxation solution with an efficient rounding heuristic which empirically gives certificates of small suboptimality. We evaluate two particular types of pairwise costs and demonstrate improvements over recent tracking methods in real-world video sequences.
Type de document :
Communication dans un congrès
CVPR 2015 - 28th IEEE Conference on Computer Vision and Pattern Recognition, Jun 2015, Boston, United States. 〈http://www.pamitc.org/cvpr15/〉
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https://hal.inria.fr/hal-01110678
Contributeur : Simon Lacoste-Julien <>
Soumis le : mercredi 28 janvier 2015 - 16:31:51
Dernière modification le : vendredi 25 mai 2018 - 12:02:06

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  • HAL Id : hal-01110678, version 1
  • ARXIV : 1408.3304

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Visesh Chari, Simon Lacoste-Julien, Ivan Laptev, Josef Sivic. On Pairwise Cost for Multi-Object Network Flow Tracking. CVPR 2015 - 28th IEEE Conference on Computer Vision and Pattern Recognition, Jun 2015, Boston, United States. 〈http://www.pamitc.org/cvpr15/〉. 〈hal-01110678〉

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