A Novel View of Color-Based Visual Tracker Using Principal Component Analysis

Kiyoshi NISHIYAMA  Xin LU  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E91-A   No.12   pp.3843-3848
Publication Date: 2008/12/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e91-a.12.3843
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Vision
visual tracking,  mean shift,  principle component analysis,  Gaussian probability density function,  

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An extension of the traditional color-based visual tracker, i.e., the continuously adaptive mean shift tracker, is given for improving the convenience and generality of the color-based tracker. This is achieved by introducing a probability density function for pixels based on the hue histogram of object. As its merits, the direction and size of the tracked object are easily derived by the principle component analysis (PCA), and its extension to three-dimensional case becomes straightforward.