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Proceedings Paper

Robust pedestrian detection and tracking in crowded scenes
Author(s): Yuriy Lypetskyy
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Paper Abstract

This paper presents a vision based tracking system developed for very crowded situations like underground or railway stations. Our system consists on two main parts - searching of people candidates in single frames, and tracking them frame to frame over the scene. This paper concentrates mostly on the tracking part and describes its core components in detail. These are trajectories predictions using KLT vectors or Kalman filter, adaptive active shape model adjusting and texture matching. We show that combination of presented algorithms leads to robust people tracking even in complex scenes with permanent occlusions.

Paper Details

Date Published: 10 September 2007
PDF: 9 pages
Proc. SPIE 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision, 676409 (10 September 2007); doi: 10.1117/12.734192
Show Author Affiliations
Yuriy Lypetskyy, JOANNEUM RESEARCH GmbH (Austria)


Published in SPIE Proceedings Vol. 6764:
Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

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