Statements in which the resource exists.
SubjectPredicateObjectContext
pubmed-article:15376893rdf:typepubmed:Citationlld:pubmed
pubmed-article:15376893lifeskim:mentionsumls-concept:C1522242lld:lifeskim
pubmed-article:15376893lifeskim:mentionsumls-concept:C0441635lld:lifeskim
pubmed-article:15376893lifeskim:mentionsumls-concept:C1442162lld:lifeskim
pubmed-article:15376893lifeskim:mentionsumls-concept:C0443288lld:lifeskim
pubmed-article:15376893lifeskim:mentionsumls-concept:C0728938lld:lifeskim
pubmed-article:15376893lifeskim:mentionsumls-concept:C1550718lld:lifeskim
pubmed-article:15376893pubmed:issue2lld:pubmed
pubmed-article:15376893pubmed:dateCreated2004-9-20lld:pubmed
pubmed-article:15376893pubmed:abstractTextWe consider data clustering problems where partial grouping is known a priori. We formulate such biased grouping problems as a constrained optimization problem, where structural properties of the data define the goodness of a grouping and partial grouping cues define the feasibility of a grouping. We enforce grouping smoothness and fairness on labeled data points so that sparse partial grouping information can be effectively propagated to the unlabeled data. Considering the normalized cuts criterion in particular, our formulation leads to a constrained eigenvalue problem. By generalizing the Rayleigh-Ritz theorem to projected matrices, we find the global optimum in the relaxed continuous domain by eigendecomposition, from which a near-global optimum to the discrete labeling problem can be obtained effectively. We apply our method to real image segmentation problems, where partial grouping priors can often be derived based on a crude spatial attentional map that binds places with common salient features or focuses on expected object locations. We demonstrate not only that it is possible to integrate both image structures and priors in a single grouping process, but also that objects can be segregated from the background without specific object knowledge.lld:pubmed
pubmed-article:15376893pubmed:languageenglld:pubmed
pubmed-article:15376893pubmed:journalhttp://linkedlifedata.com/r...lld:pubmed
pubmed-article:15376893pubmed:citationSubsetIMlld:pubmed
pubmed-article:15376893pubmed:statusMEDLINElld:pubmed
pubmed-article:15376893pubmed:monthFeblld:pubmed
pubmed-article:15376893pubmed:issn0162-8828lld:pubmed
pubmed-article:15376893pubmed:authorpubmed-author:ShiJianboJlld:pubmed
pubmed-article:15376893pubmed:authorpubmed-author:YuStella XSXlld:pubmed
pubmed-article:15376893pubmed:issnTypePrintlld:pubmed
pubmed-article:15376893pubmed:volume26lld:pubmed
pubmed-article:15376893pubmed:ownerNLMlld:pubmed
pubmed-article:15376893pubmed:authorsCompleteYlld:pubmed
pubmed-article:15376893pubmed:pagination173-83lld:pubmed
pubmed-article:15376893pubmed:dateRevised2006-11-15lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:meshHeadingpubmed-meshheading:15376893...lld:pubmed
pubmed-article:15376893pubmed:year2004lld:pubmed
pubmed-article:15376893pubmed:articleTitleSegmentation given partial grouping constraints.lld:pubmed
pubmed-article:15376893pubmed:affiliationDepartment of Computer Science, University of California at Berkeley, 549 Soda Hall, Berkeley, CA 94720-1776, USA. stellayu@cs.berkeley.edulld:pubmed
pubmed-article:15376893pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:15376893pubmed:publicationTypeComparative Studylld:pubmed
pubmed-article:15376893pubmed:publicationTypeResearch Support, U.S. Gov't, Non-P.H.S.lld:pubmed
pubmed-article:15376893pubmed:publicationTypeEvaluation Studieslld:pubmed
pubmed-article:15376893pubmed:publicationTypeValidation Studieslld:pubmed