Pii: S0031-3203(01)00150-9
نویسندگان
چکیده
In this paper, we propose and integrate two Bayesian methods, one of them for junction detection, and the other one for junction grouping. Our junction detection method relies on a probabilistic edge model and a log-likelihood test. Our junction grouping method relies on 6nding connecting paths between pairs of junctions. Path searching is performed by applying a Bayesian A∗ algorithm. Such algorithm uses both an intensity and geometric model for de6ning the rewards of a partial path and prunes those paths with low rewards. We have extended such a pruning with an additional rule which favors the stability of longer paths against shorter ones. We have tested experimentally the e:ciency and robustness of the methods in an indoor image sequence. ? 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
منابع مشابه
Gaussian mixture parameter estimation with known means and unknown class-dependent variances
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