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Article: Computer vision for RGB-D sensors: Kinect and its applications

TitleComputer vision for RGB-D sensors: Kinect and its applications
Authors
Issue Date2013
Citation
IEEE Transactions on Cybernetics, 2013, v. 43, n. 5, p. 1314-1317 How to Cite?
AbstractThe special issue of IEEE Transactions On Cybernetics is specifically dedicated to new algorithms and applications based on the Kinect or high-resolution depth and visual (RGB-D) sensors. An article entitled 'Enhanced Computer Vision with Microsoft Kinect Sensor: A Review' surveys recent Kinect-based computer vision algorithms and applications, covering various topics including preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. The main algorithmic contributions are outlined for each category of methods and their advantages or differences compared to their RGB counterparts. An overview of the challenges in this field and future research trends is given in an effort to serve as a tutorial and source of references for Kinect-based computer vision researchers.
Persistent Identifierhttp://hdl.handle.net/10722/321552
ISSN
2023 Impact Factor: 9.4
2023 SCImago Journal Rankings: 5.641
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShao, Ling-
dc.contributor.authorHan, Jungong-
dc.contributor.authorXu, Dong-
dc.contributor.authorShotton, Jamie-
dc.date.accessioned2022-11-03T02:19:42Z-
dc.date.available2022-11-03T02:19:42Z-
dc.date.issued2013-
dc.identifier.citationIEEE Transactions on Cybernetics, 2013, v. 43, n. 5, p. 1314-1317-
dc.identifier.issn2168-2267-
dc.identifier.urihttp://hdl.handle.net/10722/321552-
dc.description.abstractThe special issue of IEEE Transactions On Cybernetics is specifically dedicated to new algorithms and applications based on the Kinect or high-resolution depth and visual (RGB-D) sensors. An article entitled 'Enhanced Computer Vision with Microsoft Kinect Sensor: A Review' surveys recent Kinect-based computer vision algorithms and applications, covering various topics including preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. The main algorithmic contributions are outlined for each category of methods and their advantages or differences compared to their RGB counterparts. An overview of the challenges in this field and future research trends is given in an effort to serve as a tutorial and source of references for Kinect-based computer vision researchers.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Cybernetics-
dc.titleComputer vision for RGB-D sensors: Kinect and its applications-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TCYB.2013.2276144-
dc.identifier.pmid23955797-
dc.identifier.scopuseid_2-s2.0-84891534143-
dc.identifier.volume43-
dc.identifier.issue5-
dc.identifier.spage1314-
dc.identifier.epage1317-
dc.identifier.isiWOS:000324586700001-

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