Improved CamShift tracking algorithm based on motion detection
Yu-Hui Qui, Jianwei Zhang, Guang Lin, Yonghui Li, Dongfa Gao · 2013
The traditional Continuously Adaptive Mean Shift Algorithm (CamShift) is widely used, but its drawback is unsatisfactory performance due to counting aU pixels when calculating the color histogram and back projection using a rectangular box to select the target. We propose an improved CamShift Algorithm based on motion detection. When calculating the color histogram of a target within the rectangular box, it adds a mask layer to remove background pixels around targets. When calculating the back projection, it adds a mask layer to remove all background pixels within the window to eliminate the interference of similar color in the background. The experimental results show that this improved algorithm utilizes the color feature better and keeps the tracking right even when background interference exists.