Feature grouping in a hierarchical probabilistic network
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摘要
The goal of feature grouping is to provide efficient codings of the necessary information for much of the scene interpretation and object recognition applications in machine vision. This paper offers a sound theoretical background for feature grouping processes, using a Bayesian approach which makes explicit the world knowledge which is applied at any stage. We describe a framework which can integrate many different forms of grouping and different levels of information. We also report on a preliminary implementation within this framework to group parallel lines in a perspective image. In support of this we develop a mapping from the image uncertainty to the orientation uncertainty for the hypothesized groups.
论文关键词:feature grouping,scene interpretation,Bayesian approach
论文评审过程:Available online 10 June 2003.
论文官网地址:https://doi.org/10.1016/0262-8856(91)90049-U