Realistic face generating method based on single photo

Abstract

The invention discloses a realistic face generating method based on a single photo. The method comprises steps of firstly constructing a standard face model base, interactively selecting face feature points of an input picture and based on face profile features, matching an optimal model; secondly, via the triangle deformation and the bilinearity interpolation method, realizing texture mapping from the picture to a three-dimensional model, and by introducing an Alpha graph, realizing fusion transition from face covering textures to model neutral textures; and at last, by adopting the grid adjusting method, hierarchically adjusting the model from the whole to the details so as to achieve an objective of a realistic three-dimensional face. The method is user-friendly and requires quite few feature points; and just with one full face photo and quite few feature points, a user can participate in an autonomously finished realistic face establishing method.

Description

technical field [0001] The invention relates to a method for quickly generating a three-dimensional human face, in particular to a method for generating a realistic human face based on a single photo. Background technique [0002] Human faces are an important part of emotional expression and identity recognition. In life, we use faces to identify identities and express emotions through faces. Faces play a pivotal role in our daily lives. With the development of computer graphics, face reconstruction for specific graphics has been widely used in many fields. Constructing a three-dimensional virtual character with a realistic human face has a positive effect on enhancing the user's interest and participation initiative. In the fields of game animation, film and television advertisements, 3D campuses, digital tourist attractions, virtual locker rooms and other fields, as one of the means to improve the user's sensory experience, research on face model generation technology wi...

AI Technical Summary

Problems solved by technology

[0003] The existing rapid face generation methods mainly use 3D scanners and other equipment to obtain 3D face data. The generated model has high fidelity, but relies on a large amount of point cloud data, which requires high technical requirements and is expensive; A front and side image is used to reconstruct the face model through visual correlation theory and algorithm. This method requires manual calibration of many feature points, and the input conditions are relatively complicated.

Therefore, the traditional face model generation method has problems such as expensive equipment, complex implementation process, and insufficient real-time performance, and cannot fully meet the needs of real-time interaction in virtual scenes.

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