Abstract

Human face plays an indispensable role in emotional expression and information exchange, which attracts large number of researchers to study face recognition. Nowadays, with the rapid development of computer graphics, artificial intelligence, and other technologies, the ability of the human vision system to recognize facial expressions and facial organs is enhanced. More and more experts think about how to make the computer vision system have this capability. By combining artificial intelligence and computer graphics, this paper studies how to optimize the 3D face network model and extract geometric features for 3D face recognition. We propose a 3D face network model based on Poisson equation to realize face hole recognition and boundary preprocessing. Besides, we also establish the 3D face surface equation and equal face value extraction and enhance the face feature based on facial semantic information. We study the hole repair of 3D face model based on Poisson equation integrating semantic information and achieve the purpose of optimizing the 3D face model. After the optimization, the method is compared with mesh repair and Poisson repair, which demonstrates that our Poisson-based 3D face hole repairing model obtains the best results among compared methods.

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