A Fast Training Method for Face Detection

This paper describes a fast and simple training method for face detection based on block orientation of the gray level gradient. The gradient orientation is one of the most essential features to describe the image structure. In this paper, the detector is trained just by the positive samples from which the feature value repeat times are regarded as the values´ weight to detect. The training set is of 50 face samples. Each image is divided into a low resolution of 4 times 4 blocks to train the detector and the rate of the correct detection rate is higher than 90%.