<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-14T06:32:24Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:10230/35824" metadataPrefix="oai_dc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:10230/35824</identifier><datestamp>2025-12-18T01:21:19Z</datestamp><setSpec>com_2072_6</setSpec><setSpec>col_2072_452952</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
   <dc:title>Monocular depth ordering using perceptual occlusion cues</dc:title>
   <dc:creator>Rezaeirowshan, Babak</dc:creator>
   <dc:creator>Ballester, Coloma</dc:creator>
   <dc:creator>Haro Ortega, Gloria</dc:creator>
   <dc:subject>Monocular depth</dc:subject>
   <dc:subject>Ordinal depth</dc:subject>
   <dc:subject>Depth layering</dc:subject>
   <dc:subject>Occlusion reasoning</dc:subject>
   <dc:subject>Convexity</dc:subject>
   <dc:subject>T-junctions</dc:subject>
   <dc:subject>Boundary ownership</dc:subject>
   <dc:subject>2.1D</dc:subject>
   <dc:description>Comunicació presentada al congrés International Conference on Computer Vision Theory and Applications  celebrat del 27 al 29 de febrer de 2016 a Roma, Itàlia.</dc:description>
   <dc:description>In this paper we propose a method to estimate a global depth order between the objects of a scene using information from a single image coming from an uncalibrated camera. The method we present stems from early vision cues such as occlusion and convexity and uses them to infer both a local and a global depth order. Monocular occlusion cues, namely, T-junctions and convexities, contain information suggesting a local depth order between neighbouring objects. A combination of these cues is more suitable, because, while information conveyed by T-junctions is perceptually stronger, they are not as prevalent as convexity cues in natural images. We propose a novel convexity detector that also establishes a local depth order. The partial order is extracted in T-junctions by using a curvature-based multi-scale feature. Finally, a global depth order, i.e., a full order of all shapes that is as consistent as possible with the computed partial orders that can tolerate conflicting partial or ders is computed. An integration scheme based on a Markov chain approximation of the rank aggregation problem is used for this purpose. The experiments conducted show that the proposed method compares favorably with the state of the art.</dc:description>
   <dc:description>The authors acknowledge partial support by MICINN&#xd;
project, reference MTM2012-30772, and by GRC reference&#xd;
2014 SGR 1301, Generalitat de Catalunya.</dc:description>
   <dc:date>2018-11-22T09:50:48Z</dc:date>
   <dc:date>2018-11-22T09:50:48Z</dc:date>
   <dc:date>2016</dc:date>
   <dc:type>info:eu-repo/semantics/conferenceObject</dc:type>
   <dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
   <dc:identifier>Rezaeirowshan B, Ballester C, Haro G. Monocular depth ordering using perceptual occlusion cues. In: Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) - Volume 4; 2016 Feb 27-29; Rome, Italy. Setúbal: Scitepress; 2016. p. 431-41. DOI: 10.5220/0005726404310441</dc:identifier>
   <dc:identifier>978-989-758-175-5</dc:identifier>
   <dc:identifier>http://hdl.handle.net/10230/35824</dc:identifier>
   <dc:identifier>http://dx.doi.org/10.5220/0005726404310441</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) - Volume 4; 2016 Feb 27-29; Rome, Italy. Setúbal: Scitepress; 2016.</dc:relation>
   <dc:rights>© 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:format>application/pdf</dc:format>
   <dc:format>application/pdf</dc:format>
   <dc:publisher>SCITEPRESS – Science and Technology Publications, Lda.</dc:publisher>
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