Robust face tracking algorithm with occlusions
Zhanqing Wang, Youfu Fan, Guilin Zhang, Ruolan Hu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
We propose an adaptive model update mechanism for face tracking based on mean-shift, we employ the Kalman filter to predict a proper original position for mean shift tracking algorithm. To overcome the problem of appearance change, an adaptive modal update is introduced. We classify the occlusion problems into two main cases specified as partial occlusion and complete occlusion according to the number of similar sub blocks between object and candidate. We fuss Kalman predictor into Mean-shift tracker in case of partial occlusion, for case of full occlusion, we divide object and candidate into four parts respectively, according to the previous exact tracking result, we compute the average velocity of the target, and then check the condition for face reappearing, with which we present an efficient target search strategy to deal with full occlusion. Various tracking sequences demonstrate the superior behavior of our tracker and its robustness to appearance changes and occlusions.