Method for IR imaging target tracking based on texture feature

An IR imaging target tracking method is proposed, which integrates LBP (Local Binary Pattern) texture feature with kernel-based tracking. The confidence of each target region is calculated according to its discriminative power between the target region and local background. The target and candidate models are characterized by the kernel density estimation of LBP texture feature weighted by region confidence and distance. The similarity function between target and candidate is optimized by mean shift algorithm to realize real-time tracking. The effectiveness of the method is demonstrated by several real sequences testing.