• DocumentCode
    415610
  • Title

    Probabilistic parameter-free motion detection

  • Author

    Veit, Thomas ; Cao, Frédéric ; Bouthemy, Patrick

  • Author_Institution
    Campus de Beaulieu, IRISA/INRIA, Rennes, France
  • Volume
    1
  • fYear
    2004
  • fDate
    27 June-2 July 2004
  • Abstract
    We propose an original probabilistic parameter-free method for the detection of independently moving objects in an image sequence. We apply a probabilistic perceptual principle, the Helmholtz principle, whose main advantage is the automatization of the detection decision, by providing a light control of the number of false alarms. Not only does this method localize the moving objects but it also answers the preliminary question of the presence of motion. In particular the method works even when no assumption on motion presence is made. The algorithm is composed of three independent steps: estimation of the dominant image motion, spatial segmentation of object boundaries and independent motion detection itself We emphasize that none of these steps needs any parameter tuning. Results on real image sequences are reported and validate the proposed approach.
  • Keywords
    Helmholtz equations; boundary-value problems; image segmentation; image sequences; motion compensation; motion estimation; probability; Helmholtz principle; automatization; detection decision; false alarms; image motion estimation; motion compensation; motion detection; moving objects; object boundaries; parameter tuning; probabilistic parameter free method; probabilistic perceptual principle; real image sequences; spatial segmentation; tight control; Automatic control; Cameras; Computer vision; Image motion analysis; Image segmentation; Image sequences; Motion analysis; Motion detection; Motion estimation; Object detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-2158-4
  • Type

    conf

  • DOI
    10.1109/CVPR.2004.1315102
  • Filename
    1315102