Share Email Print
cover

Proceedings Paper

Tracking individuals in surveillance video of a high-density crowd
Author(s): Ninghang Hu; Henri Bouma; Marcel Worring
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Video cameras are widely used for monitoring public areas, such as train stations, airports and shopping centers. When crowds are dense, automatically tracking individuals becomes a challenging task. We propose a new tracker which employs a particle filter tracking framework, where the state transition model is estimated by an optical-flow algorithm. In this way, the state transition model directly uses the motion dynamics across the scene, which is better than the traditional way of a pre-defined dynamic model. Our result shows that the proposed tracker performs better on different tracking challenges compared with the state-of-the-art trackers, while also improving on the quality of the result.

Paper Details

Date Published: 7 May 2012
PDF: 8 pages
Proc. SPIE 8399, Visual Information Processing XXI, 839909 (7 May 2012); doi: 10.1117/12.918604
Show Author Affiliations
Ninghang Hu, TNO (Netherlands)
Univ. of Amsterdam (Netherlands)
Henri Bouma, TNO (Netherlands)
Marcel Worring, Univ. of Amsterdam (Netherlands)


Published in SPIE Proceedings Vol. 8399:
Visual Information Processing XXI
Mark Allen Neifeld; Amit Ashok, Editor(s)

© SPIE. Terms of Use
Back to Top