Determining Reflectance Parameters and Illumination Distribution from a Sparse Set of Images for View-dependent Image Synthesis

  • Ko Nishino ,
  • Zhengyou Zhang ,
  • Katsushi Ikeuchi

Proceedings International Conference on Computer Vision (ICCV 2001), Vancouver, Canada |

A framework for photo-realistic view-dependent image synthesis of a shiny object from a sparse set of images and a geometric model is proposed. Each image is aligned with the 3D model and decomposed into two images with regards to the reflectance components based on the intensity variation of object surface points. The view-independent surface reflection (diffuse reflection) is stored as one texture map. The view-dependent reflection (specular reflection) images are used to recover the initial approximation of the illumination distribution, and then a two step numerical minimization algorithm utilizing a simplified Torrance-Sparrow reflection model is used to estimate the reflectance parameters and refine the illumination distribution. This provides a very compact representation of the data necessary to render synthetic images from arbitrary viewpoints. We have conducted experiments with real objects to synthesize photorealistic view-dependent images within the proposed framework.