• DocumentCode
    178753
  • Title

    The Perspective-3-Point Problem When Using a Planar Mirror

  • Author

    Xianghua Ying ; Ganwen Wang ; Xiang Mei ; Sen Yang ; Hongbin Zha

  • Author_Institution
    Key Lab. of Machine Perception (Minist. of Educ.), Peking Univ., Beijing, China
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    4033
  • Lastpage
    4037
  • Abstract
    The Perspective-3-Point problem (P3P) is a classical and fundamental problem in computer vision. All possible solution sets for the P3P problem are from 1 to 4 solutions. In this paper, we propose a very simple way to reduce the ambiguity of numbers of possible solutions in P3P using a planar mirror. For three reference points, if they and their reflections in a planar mirror are both observed, we may obtain two P3P problems: One is from the three original reference points, and the other is from their reflections. A trivial procedure may be suggested: Solve for each of the two P3P problems, and then find the intersections of the two solution sets. Different from the trivial case, we propose an efficient method which employs the ratio relations of the unknowns in the two P3P problems. The ratio relations are arise from mirror reflection, and can be easily determined before solving the two P3P problems. With the ratio relations, a system of 6 equations with 3 unknowns can be determined. To solve the over-constraint problem, we utilize an efficient algorithm by finding all local minima of least-squares residual. Experiments validate our approach.
  • Keywords
    computational geometry; computer vision; P3P problems; computer vision; least-squares residual; perspective-3-point problem; planar mirror; Calibration; Cameras; Computer vision; Equations; Mirrors; Pattern recognition; Three-dimensional displays; P3P problem; Perspective-3-point problem; camera calibration; planar mirror; vanishing point;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.691
  • Filename
    6977404