Efficient Image Gradient-Based Object Localisation and Recognition

Authors:
T. N. Tan;G. D. Sullivan;K. D. Baker
Affiliations:
-;-;-
Venue:
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Year:
1996

Citing 0
Cited 4

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Abstract

This paper reports novel algorithms for the efficient localization and recognition of vehicles in traffic scenes, which eliminate the need for explicit symbolic feature extraction and matching. The algorithms make use of two a priori sources of knowledge about the scene and the objects: (i) the ground-plane constraint, and (ii) the fact that road vehicles are strongly rectilinear. The algorithms are demonstrated and tested using routine outdoor traffic images. Success with a variety of vehicles demonstrates the efficiency and robustness of context-based computer vision in road traffic scenes. The limitations of the algorithms are also addressed in the paper.