Research and Implementation of Pattern Recognition Based on Adaboost Algorithm

Pattern recognition and computer vision technology as a long-term subject of concern, which has high academic value and commercial value. Adaboost is an iterative algorithm, and its core idea is to obtain some weak classifier with a training set of training. Finally, a much stronger classifier is obtained by combining weak classifiers. In this paper, we firstly introduce the basic theory of Adaboost algorithm, and then take face recognition as an application example, the training process and the detection process were achieved respectively and independently. Experimental results show the detector based on Adaboost algorithm can accurately detect the location of the face, regardless of their positions, scale, orientation, lighting conditions, expressions, etc., and it has a smaller detection error. Specifically, the detector can effectively detect multiple faces, and it also has much higher detection accuracy