Method for estimating material reflection parameters based on images acquired by portable equipment

Abstract

The invention discloses a method for estimating a material reflection parameter based on images acquired by portable equipment. The method comprises the following steps: shooting a material ambient light image and a flash lamp image; estimating the material roughness, the specular reflection coefficient, the diffuse reflection coefficient and the normal map according to the ambient light image; calibrating the direction, the distance and the real irradiance to the camera and the light source in a per pixel manner; solving a color channel correction vector between the ambient light image and the flash light image; and determining the positions of similar pixel points based on clustering, determining the final cluster number by adopting a gradual iterative refinement mode, and endowing points in each class with the same reflection parameters. The method can be used for conveniently estimating the SVBRDF parameters of the material; and aiming at the phenomenon that some material maps estimated by a neural network at present have serious halo and the like, the method can re-estimate the reflection parameters of the material by shooting the material flash lamp image andthe ambient light image, so that the sense of reality of rendering is improved.

Description

technical field [0001] The invention relates to material reflection parameter estimation, in particular to a method for estimating material reflection parameters based on images collected by portable devices. Background technique [0002] In the real world, the appearance properties of an object under different lighting conditions and different viewing angles are determined by the material on the surface of the object. How to restore the material conveniently and efficiently is an important topic in computer graphics at present, and it is widely used in visual effects, electronics, etc. business, product design, and entertainment. However, digitally obtaining high-quality material appearance from the real world is still a challenging problem. The biggest challenge is that the material appearance in the real world has great complexity. Objects in the real world are generally composed of multiple materials, and the surface of the material has complex geometry, which will incr...

AI Technical Summary

Problems solved by technology

However, a large number of tests have shown that this method is not robust, especially on materials such as specular materials whose brightness changes drastically with angle changes, the output results have obvious artifacts on the parameter map, and sometimes the roughness and The specular reflection coefficient estimate has a large deviation from the true value

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