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2D Methods for pose invariant face recognition

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dc.contributor.author Mokoena, Ntabiseng
dc.contributor.author Djonon Tsague, Hippolyte
dc.contributor.author Helberg, A
dc.date.accessioned 2017-06-07T07:04:42Z
dc.date.available 2017-06-07T07:04:42Z
dc.date.issued 2016-12
dc.identifier.citation Mokoena, N., Djonon Tsague, H. and Helberg, A. 2016. 2D Methods for pose invariant face recognition. 2016 International Conference on Computational Science and Computational Intelligence (CSCI), 15-17 December 2016, Las Vegas, Nevada, p. 841-846 en_US
dc.identifier.isbn 978-1-5090-5510-4
dc.identifier.uri http://ieeexplore.ieee.org/document/7881456/
dc.identifier.uri DOI: 10.1109/CSCI.2016.0163
dc.identifier.uri http://hdl.handle.net/10204/9141
dc.description Copyright: 2016 EE Publishers. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. en_US
dc.description.abstract The ability to recognise face images under random pose is a task that is done effortlessly by human beings. However, for a computer system, recognising face images under varying poses still remains an open research area. Face recognition across pose is the ability of a face recognition technology (FRT) to recognise face images in different viewpoints, i.e. recognition of face images that are out of the image plane. In this research work, a short literature survey of 2D techniques which are used to correct pose are discussed.The classification of these techniques is based on three categories, (1) Real-view based matching, (2) Image space pose transformation and (3) Feature space pose transformation. This paper discuss the types of databases used, approaches to correct pose, the types of features extracted. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Worklist;18407
dc.subject Face recognition en_US
dc.title 2D Methods for pose invariant face recognition en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Mokoena, N., Djonon Tsague, H., & Helberg, A. (2016). 2D Methods for pose invariant face recognition. IEEE. http://hdl.handle.net/10204/9141 en_ZA
dc.identifier.chicagocitation Mokoena, Ntabiseng, Hippolyte Djonon Tsague, and A Helberg. "2D Methods for pose invariant face recognition." (2016): http://hdl.handle.net/10204/9141 en_ZA
dc.identifier.vancouvercitation Mokoena N, Djonon Tsague H, Helberg A, 2D Methods for pose invariant face recognition; IEEE; 2016. http://hdl.handle.net/10204/9141 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Mokoena, Ntabiseng AU - Djonon Tsague, Hippolyte AU - Helberg, A AB - The ability to recognise face images under random pose is a task that is done effortlessly by human beings. However, for a computer system, recognising face images under varying poses still remains an open research area. Face recognition across pose is the ability of a face recognition technology (FRT) to recognise face images in different viewpoints, i.e. recognition of face images that are out of the image plane. In this research work, a short literature survey of 2D techniques which are used to correct pose are discussed.The classification of these techniques is based on three categories, (1) Real-view based matching, (2) Image space pose transformation and (3) Feature space pose transformation. This paper discuss the types of databases used, approaches to correct pose, the types of features extracted. DA - 2016-12 DB - ResearchSpace DP - CSIR KW - Face recognition LK - https://researchspace.csir.co.za PY - 2016 SM - 978-1-5090-5510-4 T1 - 2D Methods for pose invariant face recognition TI - 2D Methods for pose invariant face recognition UR - http://hdl.handle.net/10204/9141 ER - en_ZA


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