Research on 3D Expression Animation Generation Method Driven by Real-time Face Data

With the rapid development of computer graphics and visual interactive technology, 3D expression animation has been widely used in film and television production, game development, virtual reality and other fields. However, the traditional 3D expression animation generation methods often rely on manual adjustment by professional animators, which is not only inefficient, but also difficult to achieve realistic results. In this regard, according to the actual application requirements, this paper will propose a set of 3D expression animation generation methods based on real-time face data, aiming at making up for many shortcomings of traditional methods and improving the practical application effect of 3D animation. Practice has proved that OpenCV class library will be used to control all kinds of image acquisition devices to obtain real-time images of human faces in the image acquisition and preprocessing stage. In the stage of facial expression recognition, it will rely on the deep neural network model to improve the recognition accuracy of facial expression features; In the stage of 3D model reconstruction, the 3D facial model will be reconstructed based on the obtained facial expression features. Finally, with the support of 3D facial model, continuous 3D expression animation is generated by renderer. The implementation of this scheme will benefit the landing and application of related technologies, and make a positive attempt for the continuous innovation, transformation and upgrading of the whole industry.