Journal article
Contour grouping with prior models
JH Elder, A Krupnik, LA Johnston
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | IEEE COMPUTER SOC | Published : 2003
Abstract
Conventional approaches to perceptual grouping assume little specific knowledge about the object(s) of interest. However, there are many applications in which such knowledge is available and useful. Here, we address the problem of finding the bounding contour of an object in an image when some prior knowledge about the object is available. We introduce a framework for combining prior probabilistic knowledge of the appearance of the object with probabilistic models for contour grouping. A constructive search technique is used to compute candidate closed object boundaries, which are then evaluated by combining figure, ground, and prior probabilities to compute the maximum a posteriori estimate..
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