A novel method of 2D articulated body tracking under self-occlusion and ambiguity

Abstract

A novel masker-less based method to track a 2D articulated body under self-occlusion and ambiguity in monocular image sequences is proposed. The proposed method applies SMC to both color and motion features. We employ a self-updated binary occlusion mask to increase accuracy in tracking. To alleviate the effect of illumination, each color body part is formed by a Gaussian mixture model in HS space, and the distribution intersection is used in distance measures of two probability distributions. Moreover, a motion cue is used to prune spurious solutions. Our technique can track the target reliably, especially in occlusion and ambiguous cases.