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Visual surveillance using deformable models of vehicles

Ferryman, J. M., Worrall, A. D., Sullivan, G.D. and Baker, K. (1997) Visual surveillance using deformable models of vehicles. Robotics and Autonomous Systems, 19 (3-4). pp. 315-335. ISSN 0921-8890

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To link to this article DOI: 10.1016/S0921-8890(97)83348-9

Abstract/Summary

This paper presents recent developments to a vision-based traffic surveillance system which relies extensively on the use of geometrical and scene context. Firstly, a highly parametrised 3-D model is reported, able to adopt the shape of a wide variety of different classes of vehicle (e.g. cars, vans, buses etc.), and its subsequent specialisation to a generic car class which accounts for commonly encountered types of car (including saloon, batchback and estate cars). Sample data collected from video images, by means of an interactive tool, have been subjected to principal component analysis (PCA) to define a deformable model having 6 degrees of freedom. Secondly, a new pose refinement technique using “active” models is described, able to recover both the pose of a rigid object, and the structure of a deformable model; an assessment of its performance is examined in comparison with previously reported “passive” model-based techniques in the context of traffic surveillance. The new method is more stable, and requires fewer iterations, especially when the number of free parameters increases, but shows somewhat poorer convergence. Typical applications for this work include robot surveillance and navigation tasks.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:19000
Uncontrolled Keywords:model-based vision, surveillance systems, robotic vision, traffic scene analysis, deformable models, shape, principal component analysis (PCA)
Publisher:Elsevier

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