Learning an image-based motion context for multiple people tracking

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 3542-3549

  Leal Taixé, Laura ^a,b   Fenzi, Michele ^b   Kuznetsova, Alina ^b   Rosenhahn, Bodo ^b   Savarese, Silvio ^c  

^a ETH ZURICH   (Switzerland)

^b LEIBNIZ UNIVERSITY HANNOVER   (Germany)

^c STANFORD UNIVERSITY   (United States)

Author keywords

image based motion context; linear programming; multiple people tracking; social force model

Indexed keywords

DECISION TREES; LINEAR PROGRAMMING; PATTERN RECOGNITION; TARGET TRACKING;

IMAGE-BASED; INTERACTION FEATURES; LEARNED DICTIONARIES; LOW-LEVEL IMAGE FEATURES; MULTIPLE PEOPLE TRACKING; PHYSICAL INTERACTIONS; SOCIAL FORCE MODELS; STATE-OF-THE-ART APPROACH;

MOTION TRACKING;

EID: 84911365771     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.453     Document Type: Conference Paper

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