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Proceedings Paper

Matching of road segments using probabilistic relaxation: a hierarchical approach
Author(s): William J. Christmas; Josef Kittler; Maria Petrou
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Paper Abstract

Probabilistic relaxation has been used previously as the basis for the development of an algorithm to match features extracted from an image with corresponding features from a model. The technique has proved very successful, especially in applications that require real- time performance. On the other hand its use has been limited to small problems, because the complexity of the algorithm varies with the fourth power of the problem size. In this paper, we show how the computational complexity can be much reduced. The matching is performed in two stages. In the first stage, only small subsets of the most salient features are used to provide an initial match. The results are used to calculate projective parameters that relate the image to the model. In the second stage, these parameters are used to simplify the matching of the entire feature sets, in a second pass of the matching algorithm.

Paper Details

Date Published: 30 June 1994
PDF: 9 pages
Proc. SPIE 2304, Neural and Stochastic Methods in Image and Signal Processing III, (30 June 1994); doi: 10.1117/12.179224
Show Author Affiliations
William J. Christmas, Univ. of Surrey (United Kingdom)
Josef Kittler, Univ. of Surrey (United Kingdom)
Maria Petrou, Univ. of Surrey (United Kingdom)


Published in SPIE Proceedings Vol. 2304:
Neural and Stochastic Methods in Image and Signal Processing III
Su-Shing Chen, Editor(s)

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