Mengnan Hu
ABSTRACT
A method for multi-angle face tracking based on multi-feature fusion and KCF algorithm is proposed in this paper. Firstly, Haar-like, MB-LBP and HOG features are combined to detect the face region, which is regarded as the initial tracking search window. Secondly, training, updating and adjusting search window size. Finally, if the tracking target is lost, face region is relocated through the multi-angle detection algorithm which can realize real-time and automatic tracking. To verify the effect, our method is compared with the traditional KCF algorithm. The results of simulation experiments show that, the method proposed can track multi-angle face of video sequences from video database in real time, the center distance error is 8.49, the overlap rate is 58.78%, and the tracking time is 55.41ms.
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