Auto Face Detection and Tracking Algorithm Combining Color and Texture Features Based on Particle Filter
Qingbo Ji · Journal of Information and Computational Science · 2014
In this paper, an auto human face detection and tracking algorithm combining color and texture features based on particle filter is proposed. Firstly, the proposed approach makes use of AdaBoost algorithm based on skin color to detect the human face, and implements the initial face location. Secondly, the particle filter algorithm based on the weighted color histogram and the histogram of oriented gradients is used to track the human face. Finally, an adaptive window size adjustment strategy can be fused under the particle filter framework to solve the problem of fixed tracking window size. The experimental results show the robustness and accuracy of the algorithm.