Independent motion segmentation and collision prediction for road vehicles

  • D. Sinclair
  • B. Boufama
Motion Segmentation and Tracking
Part of the Lecture Notes in Computer Science book series (LNCS, volume 800)


This paper presents a method for doing motion segmentation for autonomous vehicles which drive on planar surfaces. There are two distinct types of independent motion that may occur within an image sequence taken from a moving vehicle. The first generic type of independent motion is when the projected motion of points on the independent object violate the epipolar constraint. The second case is where the epipolar constraint is not violated. This paper demonstrates that it is possible to detect this second type of independent motion by looking for progressive dis-occlusion of the road. A novel collision prediction method is also given. The method predicts the projection of a corridor down which the AGV will travel. This prediction may be used for time to contact collision prediction and the corridor width embodies an estimate of the vehicles size.


Motion segmentation occlusion collision avoidance 


  1. 1.
    P.A. Beardsley, D. Sinclair, and A. Zisserman. Ego-motion from six points. Insight meeting, Catholic University Leuven, 1992.Google Scholar
  2. 2.
    P.J. Burt and et al. Object tracking with a moving camera. In Proc. 2nd Int. Conf. on Computer Vision, pages 2–12, 1989.Google Scholar
  3. 3.
    B.F. Buxton and D.W. Murray. Optic flow segmentation as an ill-posed and maximum likelihood problem. Image and Vis. Comp., 3, 4:163–169, 1985.Google Scholar
  4. 4.
    O.D. Faugeras and S.J. Maybank. Motion from point matches: Multiplicity of solutions. Int. Journal of Computer Vision, 4:225–246, 1988.Google Scholar
  5. 5.
    J.J. Koenderink and A.J. Van Doorn. Invariant properties of the motion parallax field due to the movement of rigid bodies relative to an observer. Optica Acta, 22(9):773–791, 1975.Google Scholar
  6. 6.
    H.C Longuet-Higgins. A computer algorithm for reconstructing a scene from two projections. Nature, 293(5828):133–135, 1981.Google Scholar
  7. 7.
    P.F. McLauchlan, I.D. Reid, and D.W. Murray. Coarse motion for saccade control. In Proc. 3rd BMVC, Leeds, 1992.Google Scholar
  8. 8.
    R.C. Nelson. Qualitative detection of motion by a moving observer. IJCV, 7:1:33–46, 1991.Google Scholar
  9. 9.
    R.C. Jain. Segmentation of frame sequences obtained by a moving observer. PAMI, 6:624–629, 1984.Google Scholar
  10. 10.
    D. Sinclair. Experiments in Motion and Correspondence. PhD thesis, Oxford University, 1993.Google Scholar
  11. 11.
    S. Smith. Feature based image understanding. D. phil thesis, University of Oxford, 1992.Google Scholar
  12. 12.
    P. Torr and D. Murray. Outlier detection and motion segmentation. Technical Report OUEL 1987/93, Oxford University, 1993.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • D. Sinclair
    • 1
  • B. Boufama
    • 1
  1. 1.Lifia-INRIAGrenoble CedexFrance

Personalised recommendations