Estimation of hybrid reflectance properties and shape reconstruction using the LMS method
This paper presents a new method to estimate reflectance properties of non-Lambertian surface by the least-mean-square (LMS) algorithm. In this paper, a sample sphere with the same surface properties as those of an object is used, and hybrid reflectance of an object is represented by the TorranceSparrow model. Since we know the size of the sample sphere, the intensity image of the object in the experimental setup can be generated. We determine reflectance parameters that minimize the sum squared difference of the intensity distribution between the image of the sample sphere and the generated image. By the estimated reflectance parameters, three reference images of the sample sphere are obtained from the same viewpoint with different light directions. Direct matching of the object images to the references can precisely reconstruct the shape of the object. This paper uses a plate diffuse illumination to alleviate the effects of specular spike and highlights. The experimental results show that the proposed method can estimate reflectance properties of the hybrid surface, and also recover the object shape.
reflectance property shape reconstruction lms method plate diffuse illumination photometric stereo