Human-computer interaction based on face feature localization

Abstract

Human-computer interaction is the way in which humans and machines communicate information. With the rapid development of deep learning technology, the technology of human-computer interaction has also made a corresponding breakthrough. In the past, the way human-computer interaction was mostly relied on hardware devices. Through the coordinated work of multiple sensors, people and machines can realize information interaction. However, as theoretical technology continues to mature, algorithms for human-computer interaction are also being enriched. The popularity of convolutional neural networks has made image processing problems easier to solve. Therefore, real-time human-computer interaction can be performed by using image processing, and intelligent of human-computer interaction can be realized. The main idea of this paper is to use the real-time capture of face images and video information to image the face image information. We perform feature point positioning based on the feature points of the face image. We perform expression recognition based on the feature points that are located. At the same time, we perform ray tracing for the identified human eye area. The feature points of the face and the corresponding expressions and implementation movements represent the user's use appeal. Therefore, we can analyze the user's use appeal by locating the face feature area. We define the corresponding action information for specific user face features. We extract the user's corresponding information according to the user's face features, and perform human-computer interaction according to the user's information.