Boosting nested cascade detector for multi-view face detection
Chang Huang, Haizhou Ai, Bo Wu, Shihong Lao · 2012
In this paper, a novel nested cascade detector for multi-view face detection is presented. This nested cascade is learned by Schapire and Singer’s improved boosting algorithms that use real-valued confidence-rated weak classifiers [1], where we use confidence-rated Look-Up-Table (LUT) weak classifiers based on Haar features. Experiments show the system performance is significantly improved compared with previous methods. 1.