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Wasserstein Active Contours

dc.contributor.authorRabin, Julien
HAL ID: 3181
ORCID: 0000-0003-3834-918X
dc.contributor.authorFadili, Jalal
HAL ID: 15510
dc.contributor.authorPeyré, Gabriel
HAL ID: 1211
dc.date.accessioned2011-05-27T14:28:46Z
dc.date.available2011-05-27T14:28:46Z
dc.date.issued2012
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/6338
dc.language.isoenen
dc.subjectoptimal transporten
dc.subjectactive contoursen
dc.subjectWasserstein distanceen
dc.subjectImage segmentationen
dc.subject.ddc519en
dc.titleWasserstein Active Contoursen
dc.typeCommunication / Conférence
dc.contributor.editoruniversityotherCentre de Mathématiques et de Leurs Applications (CMLA);France
dc.contributor.editoruniversityotherGroupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen (GREYC);France
dc.description.abstractenIn this paper, we propose a novel and rigorous framework for region-based active contours that combines the Wasserstein distance between statistical distributions in arbitrary dimension and shape derivative tools. To speed-up the computation and be able to handle high-dimensional features and large-scale data, we introduce an approximation of the differential of the Wasserstein distance between histograms. The framework is flexible enough to allow either minimization of the Wasserstein distance to prior distributions, or maximization of the distance between the distributions of the regions to be segmented (i.e. region competition). Numerical results reported demonstrate the advantages of the proposed optimal transport distance with respect to point-wise metrics.en
dc.identifier.citationpages2541-2544en
dc.relation.ispartoftitle19th IEEE International Conference on Image Processing (ICIP), 2012 - proceedings
dc.relation.ispartofpublnameIEEE
dc.relation.ispartofdate2012
dc.relation.isversionofdoihttp://dx.doi.org/10.1109/ICIP.2012.6467416
dc.identifier.urlsitehttp://hal.archives-ouvertes.fr/hal-00593424/fr/en
dc.description.sponsorshipprivateouien
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.ispartofisbn978-1-4673-2534-9
dc.relation.conftitle2012 IEEE International Conference on Image Processing (ICIP)
dc.relation.confdate2012-10
dc.relation.confcityOrlando
dc.relation.confcountryEtats-Unis


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