• DocumentCode
    3093435
  • Title

    Estimating 3D motion and shape of multiple objects using Hough transform

  • Author

    Tian, Tina Yu ; Shah, Mubarak

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
  • Volume
    1
  • fYear
    1994
  • fDate
    9-13 Oct 1994
  • Firstpage
    658
  • Abstract
    Presents a robust method to determine 3D motion and structure of multiple objects. Rather than segmenting the scene containing multiple motions using 3D parametric model, the authors use the general 3D motion model and exploit Hough transform and robust estimation techniques to determine motion and segmentation simultaneously for an arbitrary scene. The authors divide the input image into patches, and for each sample of the translation space and each patch, the authors compute the rotation parameters using weighted least-squares fit. Each patch votes for a sample in the five-dimensional parameter space (translation and rotation). The multiple local maxima in the parameter space naturally correspond to the multiple moving objects. The authors´ experimental results show that the proposed method is robust and relatively insensitive to noise
  • Keywords
    motion estimation; 3D motion estimation; Hough transform; five-dimensional parameter space; multiple objects; robust estimation techniques; rotation; segmentation; shape estimation; translation; weighted least-squares fit; Computer vision; Image motion analysis; Image segmentation; Layout; Motion estimation; Noise robustness; Optical computing; Optical noise; Parametric statistics; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-8186-6265-4
  • Type

    conf

  • DOI
    10.1109/ICPR.1994.576390
  • Filename
    576390