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dc.contributor.author Oliver, Maria
dc.contributor.author Haro Ortega, Gloria
dc.contributor.author Dimiccoli, Mariella
dc.contributor.author Mazin, Baptiste
dc.contributor.author Ballester, Coloma
dc.date.accessioned 2018-11-21T11:12:56Z
dc.date.available 2018-11-21T11:12:56Z
dc.date.issued 2016
dc.identifier.citation Oliver M, Haro G, Dimiccoli M, Mazin B, Ballester C. A Computational model for amodal completion. J Math Imaging Vis. 2016;56(3):511-34. DOI: 10.1007/s10851-016-0652-x
dc.identifier.issn 1573-7683
dc.identifier.uri http://hdl.handle.net/10230/35809
dc.description.abstract This paper presents a computational model to recover the most likely interpretation of the 3D scene structure from a planar image, where some objects may occlude others. The estimated scene interpretation is obtained by integrating some global and local cues and provides both the complete disoccluded objects that form the scene and their ordering according to depth. Our method first computes several distal scenes which are compatible with the proximal planar image. To compute these different hypothesized scenes, we propose a perceptually inspired object disocclusion method, which works by minimizing the Euler’s elastica as well as by incorporating the relatability of partially occluded contours and the convexity of the disoccluded objects. Then, to estimate the preferred scene, we rely on a Bayesian model and define probabilities taking into account the global complexity of the objects in the hypothesized scenes as well as the effort of bringing these objects in their relative position in the planar image, which is also measured by an Euler’s elastica-based quantity. The model is illustrated with numerical experiments on, both, synthetic and real images showing the ability of our model to reconstruct the occluded objects and the preferred perceptual order among them. We also present results on images of the Berkeley dataset with provided figure-ground ground-truth labeling.
dc.description.sponsorship The first, second and fifth authors acknowledge partial support by MICINN Project, Reference MTM2012-30772, and by GRC Reference 2014 SGR 1301, Generalitat de Catalunya. The third author is supported by a Beatriu de Pinós fellowship (Marie-Curie COFUND action).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.relation.ispartof Journal of Mathematical Imaging and Vision. 2016;56(3):511-34.
dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/s10851-016-0652-x
dc.title A Computational model for amodal completion
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1007/s10851-016-0652-x
dc.subject.keyword Perception
dc.subject.keyword Visual completion
dc.subject.keyword Disocclusion
dc.subject.keyword Bayesian model
dc.subject.keyword Relatability
dc.subject.keyword Euler elastica
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion


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