Face rendering method based on hermite interpolation neural network regression model

Abstract

The invention discloses a human face rendering method based on a Hermite interpolation neural network regression model, and belongs to the technical field of a realistic graphics real time rendering technology. The human face rendering method based on a Hermite interpolation neural network regression model includes the steps: human face area dividing, face radiancy parameter precomputation, sample data acquisition, construction and trainning of a Hermite interpolation neural network regression model, and final rendering. The human face rendering method based on a Hermite interpolation neural network regression model introduce a regression analysis theory into the human face rendering process, uses the Hermite interpolation neural network to construct a learning model, uses the sample set to train, and determines the weight matrix between each hidden layer neuron so as to effectively excavate the non-linear association between the physical attribute and he geometrical characteristic attribute of the visible points in each subarea of the face. By means of the nonlinear mapping, the human face rendering method based on a Hermite interpolation neural network regression model can quickly map the characteristic attribute of each point on the surface of the face into the color value of the point in the given lighting condition. The human face rendering method based on a Hermite interpolation neural network regression model can effectively reduce the computing scale, and can preferably realize real-time rending of realist graphics of a human face.

Description

technical field [0001] The invention belongs to the technical field of real-time rendering of realistic graphics, and in particular relates to a human face rendering method based on a Hermite interpolation neural network regression model. Background technique [0002] In recent years, realistic real-time rendering of human faces has become a research hotspot in the field of graphics. The real skin rendering effect can be obtained by using the traditional multipole dual model, but to establish this model, it is necessary to build corresponding skin measurement equipment and obtain a large number of physical parameters in advance. In the texture space, the method of convolution and linear summation of multiple Gaussian functions can also approach the subsurface scattering effect of the face very well. Compared with the traditional pole model method, this method obtains a drawing speed of about 26FPS . However, the calculation of each segment needs to complete a large number ...

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Problems solved by technology

However, the calculation of each segment requires a large number of one-dimensional convolution operations, and its computational cost is still high

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