• DocumentCode
    639436
  • Title

    Multi-view Photometric Stereo with Spatially Varying Isotropic Materials

  • Author

    Zhenglong Zhou ; Zhe Wu ; Ping Tan

  • Author_Institution
    Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    1482
  • Lastpage
    1489
  • Abstract
    We present a method to capture both 3D shape and spatially varying reflectance with a multi-view photometric stereo technique that works for general isotropic materials. Our data capture setup is simple, which consists of only a digital camera and a handheld light source. From a single viewpoint, we use a set of photometric stereo images to identify surface points with the same distance to the camera. We collect this information from multiple viewpoints and combine it with structure-from-motion to obtain a precise reconstruction of the complete 3D shape. The spatially varying isotropic bidirectional reflectance distribution function (BRDF) is captured by simultaneously inferring a set of basis BRDFs and their mixing weights at each surface point. According to our experiments, the captured shapes are accurate to 0.3 millimeters. The captured reflectance has relative root-mean-square error (RMSE) of 9%.
  • Keywords
    cameras; mean square error methods; photometric light sources; shape recognition; stereo image processing; 3D shape; BRDF; RMSE; captured reflectance; data capture setup; digital camera; handheld light source; mixing weights; multiview photometric stereo technique; photometric stereo images; root-mean-square error; spatially varying isotropic bidirectional reflectance distribution function; spatially varying isotropic materials; spatially varying reflectance; structure-from-motion; surface points; Azimuth; Image reconstruction; Light sources; Lighting; Shape; Surface reconstruction; Three-dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
  • Conference_Location
    Portland, OR
  • ISSN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2013.195
  • Filename
    6619039