Natural Feature Recognition of Multi Pose Face Images based on Augmented Reality

Abstract

Traditional face feature recognition methods have a few problems, such as low accuracy of image feature recognition and high time consumption of image feature recognition. This paper introduces augmented reality technology to realize natural feature recognition of multi pose face images. The multi pose features of face image are obtained by augmented reality technology, the color normalization of face image is realized by gamma algorithm, and the natural features of multi pose face image are extracted by three-dimensional registration technology. The feature error reconstruction of multi pose face image is realized according to sparse representation, the face image samples are projected into the optimal discriminant vector space by using two-dimensional linear discriminant analysis algorithm, and the natural feature recognition of multi pose face image is completed according to augmented reality technology. The experimental results show that the comprehensive accuracy of facial image expression recognition is as high as 95%, and the average error rate of natural feature recognition is only 3%; The time taken for feature recognition is only 3.5s, which shows that the method used in this study has higher efficiency of natural feature recognition of face image.