Study on Bhattacharyya Coefficients within Mean-Shift Framework and its Application

  • Authors:

  • Song Peng;Jie Yang;K. Zhou

  • Affiliations:

  • Electronic Information Engineering College, Henan University of Science and Technology, 471039, Luoyang, People’s Republic of China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030, Shanghai, People’s Republic of China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030, Shanghai, People’s Republic of China

  • Venue:
  • Soft Computing - A Fusion of Foundations, Methodologies and Applications
  • Year:
  • 2006

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Abstract

The classic mean-shift tracker has no integrated scale adaptation, which limits its performance in tracking variable scale object as wel l as the object with severe motions. Based on the variation analysis of Bhattacharyya coefficient within mean-shift framework, the sufficient conditions for accurate tracking of object with scale changes are presented. We propose that the changes of object scale and position within the region of previous tracking window will not impact the localization accuracy of mean-shift tracker. Based on our findings, a novel backward tracking method is introduced to solve scaling problem, and the solution of dealing with the severe object motions is also discussed by integrating mean-shift tracker into the low-resolution matching scheme.