Dynamic Weights and Pre-partitioning Real-Adaboost Face Detection Algorithm
Xiang Enning · Jisuanji gongcheng · 2007
This paper proposes a novel human face detection algorithm based on real Adaboost algorithm.Policy that calculates in advance the partitioning of Haar-like feature weak classifiers in sample input space and updating training face samples’ weights dynamically is adopted.This algorithm reduces training time cost greatly compared with classical real-Adaboost algorithm.In addition,it speeds up strong classifier converging,reduces the number of weak classifiers and decreases detecting time.