Face Recognition across Pose on Video Using Eigen Light-Fields
We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fie...
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| creator | Wibowo, M. E. Tjondronegoro, D. |
| description | We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fields within which the classification takes place. We modify the original light-field projection and found that it is more robust in the proposed system. Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video. |
| doi_str_mv | 10.1109/DICTA.2011.96 |
| format | Conference Proceeding |
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Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video.</description><identifier>ISBN: 145772006X</identifier><identifier>ISBN: 9781457720062</identifier><identifier>EISBN: 9780769545882</identifier><identifier>EISBN: 0769545882</identifier><identifier>DOI: 10.1109/DICTA.2011.96</identifier><language>eng</language><publisher>IEEE</publisher><subject>Active appearance model ; Face ; Face recognition ; Hidden Markov models ; light-fields ; Manifolds ; pose ; Probes ; Shape ; video</subject><ispartof>2011 International Conference on Digital Image Computing: Techniques and Applications, 2011, p.536-541</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6128716$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6128716$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wibowo, M. E.</creatorcontrib><creatorcontrib>Tjondronegoro, D.</creatorcontrib><title>Face Recognition across Pose on Video Using Eigen Light-Fields</title><title>2011 International Conference on Digital Image Computing: Techniques and Applications</title><addtitle>dicta</addtitle><description>We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fields within which the classification takes place. We modify the original light-field projection and found that it is more robust in the proposed system. Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video.</description><subject>Active appearance model</subject><subject>Face</subject><subject>Face recognition</subject><subject>Hidden Markov models</subject><subject>light-fields</subject><subject>Manifolds</subject><subject>pose</subject><subject>Probes</subject><subject>Shape</subject><subject>video</subject><isbn>145772006X</isbn><isbn>9781457720062</isbn><isbn>9780769545882</isbn><isbn>0769545882</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjE9LxDAUxCMiqGuPnrzkC7S-lzb_LsJSt7pQUKSKtyVNX2tkbaXpxW9vQWcOw49hhrFrhAwR7O39vmy2mQDEzKoTllhtQCsrC2mMOGWXWEitBYB6P2dJjJ-wSim7Ti_YXeU88Rfy0zCGJUwjd36eYuTPUyS-4lvoaOKvMYwD34WBRl6H4WNJq0DHLl6xs94dIyX_uWFNtWvKx7R-etiX2zoNFpaUjPN9n5PwSF5YMi0Ji64QYm0kdhZ0jz1Au5pa5QshvSXQnXSt1rnJN-zm7zYQ0eF7Dl9u_jkoFEajyn8BwzxIfQ</recordid><startdate>201112</startdate><enddate>201112</enddate><creator>Wibowo, M. E.</creator><creator>Tjondronegoro, D.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201112</creationdate><title>Face Recognition across Pose on Video Using Eigen Light-Fields</title><author>Wibowo, M. E. ; Tjondronegoro, D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-e8acff3e2c1ec29e8be291a422e8a51d907f1f00b0b0eb6c425c9e07d5ab77383</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Active appearance model</topic><topic>Face</topic><topic>Face recognition</topic><topic>Hidden Markov models</topic><topic>light-fields</topic><topic>Manifolds</topic><topic>pose</topic><topic>Probes</topic><topic>Shape</topic><topic>video</topic><toplevel>online_resources</toplevel><creatorcontrib>Wibowo, M. E.</creatorcontrib><creatorcontrib>Tjondronegoro, D.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wibowo, M. E.</au><au>Tjondronegoro, D.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Face Recognition across Pose on Video Using Eigen Light-Fields</atitle><btitle>2011 International Conference on Digital Image Computing: Techniques and Applications</btitle><stitle>dicta</stitle><date>2011-12</date><risdate>2011</risdate><spage>536</spage><epage>541</epage><pages>536-541</pages><isbn>145772006X</isbn><isbn>9781457720062</isbn><eisbn>9780769545882</eisbn><eisbn>0769545882</eisbn><abstract>We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fields within which the classification takes place. We modify the original light-field projection and found that it is more robust in the proposed system. Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video.</abstract><pub>IEEE</pub><doi>10.1109/DICTA.2011.96</doi><tpages>6</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Active appearance model Face Face recognition Hidden Markov models light-fields Manifolds pose Probes Shape video |
| title | Face Recognition across Pose on Video Using Eigen Light-Fields |
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