Analysis of Accuracy Rate of Distributed Virtual Reality Face Recognition Based on Personal Intelligent Terminal

Abstract

Due to the fact that problem occurs to the traditional algorithm in the internal change process of the sample set, this paper proposes a distributed virtual reality face recognition algorithm based on the personal intelligent terminal. By the utilization of the face image library with multiple description functions through expansion, the pixel intensity of the face image has data information, the original face image can be used to generate a face image with higher intensity pixels, and the mirror image can increase the detailed data information of the image. By effectively combining source domain images with initialization images, a scalable image set can be generated. According to parameter-free modeling, the image can be extended as a personal intelligent terminal. The test sample images of the same category and different source domains can form an image set and finally use the residual discriminant function to complete the face recognition. Finally, the results of the experimental analysis show that the distributed virtual reality face recognition accuracy analysis method proposed in this paper can not only build a face image database with multiple reconstruction functions but also effectively use the correlation within the face samples to improve the accuracy of face recognition and implement face recognition. Compared with other facial recognition algorithms, this algorithm has higher recognition accuracy and faster recognition speed.