Hybrid algorithm of object tracking based on color distribution

被引:0
作者
Lu, Xiao-Peng [1 ,2 ]
Yin, Xue-Min [1 ,2 ]
Zou, Mou-Yan [1 ]
机构
[1] Institute of Electronics, Chinese Academy of Sciences
[2] Graduate University, Chinese Academy of Sciences
来源
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2008年 / 30卷 / 02期
关键词
Bhattacharyya coefficient; Color histogram distribution; Mean shift; Object tracking; Particle filter;
D O I
10.3724/sp.j.1146.2006.01090
中图分类号
学科分类号
摘要
Though traditional mean shift method has the virtue of simplicity and availability, it does not work well when the target gets an occlusion. In the meanwhile, particle filter can solve this problem easily. Unfortunately, its performance relies heavily on the numbers of the used particles. It makes the tracking technique by particle filtering have difficulty in satisfying the requirement of real time computing. To settle the problem, this article brings about a hybrid algorithm by combining the mean shift and the particle filter tracking technique on the basis of the color histogram distribution. By adopting the strategy that the number of particles is adaptively determined, it amalgamates the virtues of the two techniques. It reduces the computational cost and ensures the performance simultaneously. The experimental results show that the proposed method is effective and robust.
引用
收藏
页码:259 / 262
页数:3
相关论文
共 6 条
[1]  
Comaniciu D., Ramesh V., Meer P., Real-time tracking of non-rigid using mean shift, IEEE Int'l Proc. of the Computer Vision and Pattern Recognition, 2, pp. 142-149, (2000)
[2]  
Comaniciu D., Meer P., Mean shift: A robust approach toward feature space analysis, IEEE Trans. on Pattern Anal. Mach. Intell., 24, 5, pp. 603-619, (2002)
[3]  
Collins R., Mean-shift blob tracking through scale space, Proc IEEE Conf. Comp. Vision Pattern Recognition, 2, pp. 234-240, (2003)
[4]  
Isard M., Blake A., Condensation-conditional density propagation for visual tracking, International Journal of Computer Vision, 29, 1, pp. 5-28, (1998)
[5]  
Nummiaro K., Koller-Meier E., van Gool L., An adaptive color-based particle filter, Image and Vision Computing, 21, 1, pp. 99-110, (2003)
[6]  
Cheng J., Zhou Y., Cai N., Yang J., Infrared object tracking based on particle filters, Infrared Millim. Waves, 25, 2, pp. 113-117, (2006)