Robust Tracking of Walking Persons by Elite-Type Particle Filters and RGB-D Images

In this paper, we propose a robust real-time tracking system using RGB-D image sequence which are obtained through stereo camera. We apply ‘Elite-type’ particle filter, which is novel structure of particle filter, for tracking multiple persons. In Elite-type particle filter, to be robust to change of appearance and partial occlusion, likelihood is designed based on histogram and each particle possess their own model histogram. The system assign this particle filter to each person, and estimate state of the target person which vary from frame to frame. Furthermore, the system is able to measure the height of person’s head, which is effective for analysis human behavior. Real-time tracking performance of multiple persons was confirmed by experiments which simulating a real shop.

[1]  Michael J. Swain,et al.  Indexing via color histograms , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[2]  Paul W. Fieguth,et al.  Color-based tracking of heads and other mobile objects at video frame rates , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[3]  M. Worring,et al.  Occlusion robust adaptive template tracking , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[4]  A. Hampapur,et al.  Smart video surveillance: exploring the concept of multiscale spatiotemporal tracking , 2005, IEEE Signal Processing Magazine.

[5]  Hironobu Fujiyoshi,et al.  Integration of Image and ID-POS in ISZOT for Behavior Analysis of Shoppers , 2014 .

[6]  Wen Gao,et al.  Online selecting discriminative tracking features using particle filter , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[7]  Joochan Sohn,et al.  Deployment of a service robot to help older people , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Luc Van Gool,et al.  An adaptive color-based particle filter , 2003, Image Vis. Comput..

[9]  Yutaka Satoh,et al.  Hybrid Feature and Adaptive Particle Filter for Robust Object Tracking , 2011 .