2003
DOI: 10.1016/s0262-8856(03)00073-8
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Dynamic trees for image modelling

Abstract: This paper introduces a new class of image model which we call dynamic trees or DTs. A dynamic tree model specifies a prior over structures of trees, each of which is a forest of one or more tree-structured belief networks (TSBN). In the literature standard tree-structured belief network models have been found to produce "blocky" segmentations when naturally occurring boundaries within an image did not coincide with those of the subtrees in the rigid fixed structure of the network. Dynamic trees have a flexibl… Show more

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Cited by 12 publications
(13 citation statements)
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“…Grammars, and related rule-based systems, provide one flexible family of hierarchical representations (Tenenbaum and Barrow 1977;Bienenstock et al 1997). For example, several different models impose distributions on hierarchical tree-structured segmentations of the pixels composing simple scenes (Adams and Williams 2003;Storkey and Williams 2003;Siskind et al 2004;Hinton et al 2000;Jin and Geman 2006). In addition, an image parsing (Tu et al 2005) framework has been proposed which explains an image using a set of regions generated by generic or object-specific processes.…”
Section: Introductionmentioning
confidence: 99%
“…Grammars, and related rule-based systems, provide one flexible family of hierarchical representations (Tenenbaum and Barrow 1977;Bienenstock et al 1997). For example, several different models impose distributions on hierarchical tree-structured segmentations of the pixels composing simple scenes (Adams and Williams 2003;Storkey and Williams 2003;Siskind et al 2004;Hinton et al 2000;Jin and Geman 2006). In addition, an image parsing (Tu et al 2005) framework has been proposed which explains an image using a set of regions generated by generic or object-specific processes.…”
Section: Introductionmentioning
confidence: 99%
“…Although the proposed model is more complex than the original GSM, in fact we show that inference is straightforward using standard tools of expectation maximization (Dempster, Laird, & Rubin, 1977) and Markov chain Monte Carlo sampling. Closely related assignment problems have been posed and solved using similar techniques, in a different class of image model known as dynamical tree modeling (Williams & Adams, 1999;Adams & Williams, 2003) and in credibility networks (Hinton, Ghahramani, & Teh, 1999).…”
Section: Bottom-up and Top-down Statistics Of Imagesmentioning
confidence: 99%
“…Williams and Adams (1999) suggested using Gibbs sampling to solve a similar assignment problem in the context of dynamic tree models. Variational approximations have also been considered in this context (Adams & Williams, 2003;Hinton et al, 1999).…”
Section: Solving the Assignment Problemmentioning
confidence: 99%
“…Djamdji et al 1993;Zheng & Chellappa 1993;Adams & Williams 2003;Zitová & Flusser 2003;Paulson et al 2010). Structural patterns observed in astronomical images often do not have a defined or even preferred shape, which is an aspect relied upon in a number of the existing object recognition algorithms (e.g., Agarwal et al 2003).…”
Section: Introductionmentioning
confidence: 99%