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- Publisher Website: 10.1109/TCYB.2013.2265378
- Scopus: eid_2-s2.0-84890399408
- PMID: 23807480
- WOS: WOS:000324586700002
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Article: Enhanced computer vision with Microsoft Kinect sensor: A review
Title | Enhanced computer vision with Microsoft Kinect sensor: A review |
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Authors | |
Keywords | Computer vision Depth image Information fusion Kinect sensor |
Issue Date | 2013 |
Citation | IEEE Transactions on Cybernetics, 2013, v. 43, n. 5, p. 1318-1334 How to Cite? |
Abstract | With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers. © 2013 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/321543 |
ISSN | 2021 Impact Factor: 19.118 2020 SCImago Journal Rankings: 3.109 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Han, Jungong | - |
dc.contributor.author | Shao, Ling | - |
dc.contributor.author | Xu, Dong | - |
dc.contributor.author | Shotton, Jamie | - |
dc.date.accessioned | 2022-11-03T02:19:39Z | - |
dc.date.available | 2022-11-03T02:19:39Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | IEEE Transactions on Cybernetics, 2013, v. 43, n. 5, p. 1318-1334 | - |
dc.identifier.issn | 2168-2267 | - |
dc.identifier.uri | http://hdl.handle.net/10722/321543 | - |
dc.description.abstract | With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers. © 2013 IEEE. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Cybernetics | - |
dc.subject | Computer vision | - |
dc.subject | Depth image | - |
dc.subject | Information fusion | - |
dc.subject | Kinect sensor | - |
dc.title | Enhanced computer vision with Microsoft Kinect sensor: A review | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TCYB.2013.2265378 | - |
dc.identifier.pmid | 23807480 | - |
dc.identifier.scopus | eid_2-s2.0-84890399408 | - |
dc.identifier.volume | 43 | - |
dc.identifier.issue | 5 | - |
dc.identifier.spage | 1318 | - |
dc.identifier.epage | 1334 | - |
dc.identifier.isi | WOS:000324586700002 | - |