Mean-Shift tracking algorithm based on background weighted update approach.

In order to solve the problems of background interference in the Mean-Shift tracking algorithm, this paper proposed an improved algorithm based on color and texture blending characteristics and background weighted update approach. The original RGB image was converted into the HSV color space, then color feature was extracted in the H, S channel and texture feature was extracted based on the LBP descriptor in the V channel. Base on this, this paper established the color-texture histogram of the object region and background. During object tracking, it updated the background region using weighted update approach according to the Bhattacharyya coefficient. The extensive experimental results show that, compared with the algorithm adopting the full background update approach with color or color-texture features, the improved algorithm makes full use of color and texture features and adopts weighted updated background region, and has a higher level of reliability and robustness and better execution efficiency. [ABSTRACT FROM AUTHOR]