• DocumentCode
    594729
  • Title

    Probabilistic depth map fusion for real-time multi-view stereo

  • Author

    Duan Yong ; Pei Mingtao ; Jia Yunde

  • Author_Institution
    Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    368
  • Lastpage
    371
  • Abstract
    In this paper we propose a probabilistic method for fusing depth maps in real time for wide-baseline situation. We treat the depth map fusion as a problem of probability density function (pdf) estimation. The original point cloud, instead of the reprojected depth map, is used to estimate the pdf, and a mathematical expectation computation method is proposed to reduce the complexity of the method. Experimental results show that the proposed method can get the fused depth map in real time, and is very promising for fusing depth maps from multiple depth cameras with sparsely distributed viewpoints.
  • Keywords
    cameras; computational complexity; image fusion; probability; real-time systems; stereo image processing; complexity reduction; mathematical expectation computation method; multiple depth cameras; pdf estimation; point cloud; probabilistic depth map fusion; probabilistic method; probability density function estimation; real-time multiview stereo; Cameras; Complexity theory; Estimation; Gaussian distribution; Probabilistic logic; Probability density function; Real-time systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460148