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| With the development of virtual reality and augmented reality (AR) technology, new types of social media continue to emerge and develop rapidly. One of the most important technologies of these social media applications is to generate a virtual image similar to that for users. Existing virtual image generation technologies are mainly divided into methods based on 3D scanning equipment and methods based on model library matching. Among them, the method based on the three-dimensional scanning device has high requirements on the device, which is not convenient to use and popularize; and the method based on the model library matching method has small individual differences in results. In order to solve the shortcomings of the existing methods, this paper proposes a method for directly generating a virtual image based on a two-dimensional image and generates an exclusive virtual image with personal characteristics for the user.This paper proposes a virtual image generation method based on web 3D face reconstruction and 3D model texture reconstruction. Use Tensorflow.js to transform the trained deep learning model into a format that can be recognized by the browser and predict the 3D face information and facial feature points on the web. Then, based on Delaunay triangulation and image affine transformation, a virtual image texture is generated for the model.The experimental results show that the method proposed in this paper can generate personalized and exclusive three-dimensional avatars based on the user's two-dimensional face information. It provides a feasibility reference for web-based virtual image related research. |
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| Keywords:avatar; augmented reality; facial fusion |
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