Vehicle Segmentation and Tracking from a Low-Angle Off-Axis Camera

  • Authors:
  • Neeraj K. Kanhere;Shrinivas J. Pundlik;Stanley T. Birchfield

  • Affiliations:
  • Clemson University;Clemson University;Clemson University

  • Venue:
  • CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
  • Year:
  • 2005

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Abstract

We present a novel method for visually monitoring a highway when the camera is relatively low to the ground and on the side of the road. In such a case, occlusion and the perspective effects due to the heights of the vehicles cannot be ignored. Features are detected and tracked throughout the image sequence, and then grouped together using a multi-level homography, which is an extension of the standard homography to the low-angle situation. We derive a concept called the relative height constraint that makes it possible to estimate the 3D height of feature points on the vehicles from a single camera, a key part of the technique. Experimental results on several different highways demonstrate the systemýs ability to successfully segment and track vehicles at low angles, even in the presence of severe occlusion and significant perspective changes.