A Multi-view Approach to Object Tracking in a Cluttered Scene Using Memory

In this paper, we propose a new multi-view approach to object tracking method that adapts itself to suddenly changing appearance. The proposed method is based on color-based particle filtering. A short-term memory and a global appearance memory are introduced to handle sudden appearance changes and occlusions of the object of interest in multi-camera environments. A new target model update method is implemented for multiple camera views. Our method is robust and versatile for a modest computational cost. Desirable tracking results are obtained.

[1]  Katja Nummiaro.  A Color-based Particle Filter , 2002 .

[2]  Luc Van Gool,et al.  Color-Based Object Tracking in Multi-camera Environments , 2003, DAGM-Symposium.

[3]  Mohamed S. Kamel,et al.  Image Analysis and Recognition , 2014, Lecture Notes in Computer Science.

[4]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[5]  Mohan M. Trivedi,et al.  Active Camera Networks and Semantic Event Databases for Intelligent Environments , 2002 .

[6]  Hang-Bong Kang,et al.  Short-Term Memory-Based Object Tracking , 2004, ICIAR.

[7]  Dorin Comaniciu,et al.  Adaptive Resolution System for Distributed Surveillance , 2002, Real Time Imaging.