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Conference Paper: A new high resolution depth map estimation system using stereo vision and depth sensing device

TitleA new high resolution depth map estimation system using stereo vision and depth sensing device
Authors
KeywordsDepth estimation system
High resolution
Kinect
Stereo vision
Issue Date2013
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1002748
Citation
The IEEE 9th International Colloquium on Signal Processing and its Applications (CSPA 2013), Kuala Lumpur, Malaysia, 8-10 March 2013. In Conference Proceedings, 2013, p. 49-53 How to Cite?
AbstractDepth map estimation is a classical problem in computer vision. Conventional depth estimation relies on stereo/multi-view matching or depth sensing devices alone. In this paper, we propose a system which addresses high resolution and high quality depth estimation based on joint fusion of stereo and Kinect data. The problem is formulated as a maximum a posteriori probability (MAP) estimation problem and reliability of two devices are derived. The depth map estimated is further refined by color image guided depth matting and a 2D polynomial regression (LPR)-based filtering. Experimental results show that our system can provide high quality and resolution depth map, which complements the strengths of stereo vision and Kinect depth sensor. © 2013 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/189921
ISBN

 

DC FieldValueLanguage
dc.contributor.authorZhang, Sen_US
dc.contributor.authorWang, Cen_US
dc.contributor.authorChan, SCen_US
dc.date.accessioned2013-09-17T15:01:18Z-
dc.date.available2013-09-17T15:01:18Z-
dc.date.issued2013en_US
dc.identifier.citationThe IEEE 9th International Colloquium on Signal Processing and its Applications (CSPA 2013), Kuala Lumpur, Malaysia, 8-10 March 2013. In Conference Proceedings, 2013, p. 49-53en_US
dc.identifier.isbn978-1-4673-5609-1-
dc.identifier.urihttp://hdl.handle.net/10722/189921-
dc.description.abstractDepth map estimation is a classical problem in computer vision. Conventional depth estimation relies on stereo/multi-view matching or depth sensing devices alone. In this paper, we propose a system which addresses high resolution and high quality depth estimation based on joint fusion of stereo and Kinect data. The problem is formulated as a maximum a posteriori probability (MAP) estimation problem and reliability of two devices are derived. The depth map estimated is further refined by color image guided depth matting and a 2D polynomial regression (LPR)-based filtering. Experimental results show that our system can provide high quality and resolution depth map, which complements the strengths of stereo vision and Kinect depth sensor. © 2013 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1002748-
dc.relation.ispartofInternational Colloquium on Signal Processing and Its Applications (CSPA) Proceedingsen_US
dc.rightsInternational Colloquium on Signal Processing and Its Applications (CSPA) Proceedings. Copyright © IEEE.-
dc.rights©2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectDepth estimation system-
dc.subjectHigh resolution-
dc.subjectKinect-
dc.subjectStereo vision-
dc.titleA new high resolution depth map estimation system using stereo vision and depth sensing deviceen_US
dc.typeConference_Paperen_US
dc.identifier.emailZhang, S: szjeff@eee.hku.hken_US
dc.identifier.emailWang, C: cwang@eee.hku.hk-
dc.identifier.emailChan, SC: ascchan@hkucc.hku.hk-
dc.identifier.authorityChan, SC=rp00094en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/CSPA.2013.6530012-
dc.identifier.scopuseid_2-s2.0-84881062586-
dc.identifier.hkuros225080en_US
dc.identifier.hkuros225397-
dc.identifier.spage49en_US
dc.identifier.epage53en_US
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 131104-

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