Visible/infrared dual-channel target tracking based on weighted mean-shift

According to the visible and infrared image sequences, when tracking in every frame, color features of visible image, vertical projective image and horizontal projective image features of infrared image are extracted. The weight in each channel was calculated with Bhattacharyya coefficient, and the weighted mean-shift tracking algorithm in dual-channel videos was derived. So visible/infrared dual-channel target tracking algorithm based on weighted mean-shift was proposed to improve tracking performance while luminance of object is changed. The proposed algorithm can effectively use the better information of each channel, for it makes the channel whose Bhattacharyya coefficient is higher have higher weight. The experiment in object tracking demonstrates that the proposed algorithm overall performance outperforms one channel(visible or infrared) target tracking algorithm based on mean-shift, and it almost remains the tracking performance when luminance of object is changed.