Robust kernel-based tracking algorithm with background contrasting

The mean-shift algorithm has achieved considerable success in object tracking due to its simplicity and efficiency. Color histogram is a common feature in the description of an object. However, the kernel-based color histogram may not have the ability to discriminate the object from clutter background. To boost the discriminating ability of the feature, based on background contrasting, this letter presents an improved Bhattacharyya similarity metric for mean-shift tracking. Experiments show that the proposed tracker is more robust in relation to background clutter.