The human face detection algorithms based on adaboost

The purpose of this paper is to use the latest real-time feature detection algorithms, presented by Paul Viola ([1]), to implement a fast human face detection system. Through the experiment, we try to get the optimal parameters to construct a human face detector with high detection speed and detection rate. Other than the implementation of the algorithms developed by Paul, we also develops a method for image data preprocess of the training system, a quick image scanning algorithm, an algorithm for simple classifier initialization and its optimization. Finally, we have an analysis on the issue of feature selection with different system parameters and the detection result of the whole system.