Model-Based Localisation and Recognition of Road Vehicles

  • Authors:
  • T. N. Tan;G. D. Sullivan;K. D. Baker

  • Affiliations:
  • Department of Computer Science, University of Reading, Reading RG6 2AY, England.;Department of Computer Science, University of Reading, Reading RG6 2AY, England.;Department of Computer Science, University of Reading, Reading RG6 2AY, England.

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 1998

Quantified Score

Hi-index 0.00

Visualization

Abstract

Objects are often constrained to lie on a known plane. This paperconcerns the pose determination and recognition of vehicles in trafficscenes, which under normal conditions stand on the ground-plane. Theground-plane constraint reduces the problem of localisation and recognitionfrom 6 dof to 3 dof.The ground-plane constraint significantly reduces the pose redundancy of2D image and 3D model line matches. A form of the generalised Houghtransform is used in conjuction with explicit probability-based votingmodels to find consistent matches and to identify the approximate poses. Thealgorithms are applied to images of several outdoor traffic scenes andsuccessful results are obtained. The work reported in this paper illustratesthe efficiency and robustness of context-based vision in a practicalapplication of computer vision.Multiple cameras may be used to overcome the limitations of a singlecamera. Data fusion in the proposed algorithms is shown to be simple andstraightforward.