A model update scheme of color-based particle filter for multi-color object tracking

Color-invariance property of objects is effectively employed for developing non-rigid object tracking algorithms in the field of computer vision. This paper develops a novel color-based tracking algorithm for non-rigid 3-D objects with multiple colors. Especially, the proposed particle filter method can track the targets even if the appearance /disappearance of color regions were occurred by self-occlusion and pose variation like self-rotation. The basic idea is closely related to the rules of proximity and common fate in grouping mechanism in human psychology, and a new model updating scheme is introduced. The effective results by the proposed method are obtained by comparing it with other color-based particle filters.

[1]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[2]  Gary Bradski,et al.  Computer Vision Face Tracking For Use in a Perceptual User Interface , 1998 .

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

[4]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

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

[6]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[7]  Takayuki Okatani,et al.  Object tracking by the mean-shift of regional color distribution combined with the particle-filter algorithms , 2004, ICPR 2004.

[8]  Yuan Li,et al.  Tracking in Low Frame Rate Video: A Cascade Particle Filter with Discriminative Observers of Different Lifespans , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  藤吉 弘亘.  (第6回)ねらった被写体を逃がさない : 物体追跡技術(次世代ディジタルカメラ/ディジタルムービーを予測する) , 2008 .

[10]  Nozomu Hamada,et al.  Robust concolor object tracking against illumination change using PCA in color space , 2009, 2009 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS).

[11]  Shihong Lao,et al.  Multiple Human Tracking Based on Multi-view Upper-Body Detection and Discriminative Learning , 2010, 2010 20th International Conference on Pattern Recognition.

[12]  Junji Yamato,et al.  Memory-Based Particle Filter for Tracking Objects with Large Variation in Pose and Appearance , 2010, ECCV.

[13]  Suk-Ho Lee,et al.  Illumination change adaptive tracking based on color centroid shifting , 2011 .

[14]  Irene Y. H. Gu,et al.  Robust Visual Object Tracking Using Multi-Mode Anisotropic Mean Shift and Particle Filters , 2011, IEEE Transactions on Circuits and Systems for Video Technology.