• DocumentCode
    254436
  • Title

    Exploiting Shading Cues in Kinect IR Images for Geometry Refinement

  • Author

    Gyeongmin Choe ; Jaesik Park ; Yu-Wing Tai ; In So Kweon

  • Author_Institution
    Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    3922
  • Lastpage
    3929
  • Abstract
    In this paper, we propose a method to refine geometry of 3D meshes from the Kinect fusion by exploiting shading cues captured from the infrared (IR) camera of Kinect. A major benefit of using the Kinect IR camera instead of a RGB camera is that the IR images captured by Kinect are narrow band images which filtered out most undesired ambient light that makes our system robust to natural indoor illumination. We define a near light IR shading model which describes the captured intensity as a function of surface normals, albedo, lighting direction, and distance between a light source and surface points. To resolve ambiguity in our model between normals and distance, we utilize an initial 3D mesh from the Kinect fusion and multi-view information to reliably estimate surface details that were not reconstructed by the Kinect fusion. Our approach directly operates on a 3D mesh model for geometry refinement. The effectiveness of our approach is demonstrated through several challenging real-world examples.
  • Keywords
    cameras; image capture; image fusion; information filtering; infrared imaging; mesh generation; 3D mesh model; Kinect IR camera; Kinect IR image capture; Kinect fusion; albedo; geometry refinement; image filtering; light source; lighting direction; multiview information; natural indoor illumination; near light IR shading model; shading cues exploitation; surface details estimation; surface normal; surface points; Cameras; Estimation; Geometry; Light sources; Lighting; Mathematical model; Three-dimensional displays; IR; Infrared; Kinect; Refinement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPR.2014.501
  • Filename
    6909896