Personalized facial attractiveness prediction
We present a fully automatic approach to learning the personal facial attractiveness preferences of individual users directly from example images. The target application is computer assisted search of partners in online dating services. The proposed approach is based on the use of epsiv-SVMs to lear...
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| creator | Whitehill, J. Movellan, J.R. |
| description | We present a fully automatic approach to learning the personal facial attractiveness preferences of individual users directly from example images. The target application is computer assisted search of partners in online dating services. The proposed approach is based on the use of epsiv-SVMs to learn a regression function that maps low level image features onto attractiveness ratings. We present empirical results based on a dataset of images collected from a large online dating site. Our system achieved correlations of up to 0.45 (Pearson correlation) on the attractiveness predictions for individual users. We show evidence that the approach learned not just a universal sense of attraction shared by multiple users, but capitalized on the preferences of individual subjects. Our results are promising and could already be used to facilitate the personalized search of partners in online dating. |
| doi_str_mv | 10.1109/AFGR.2008.4813332 |
| format | Conference Proceeding |
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The target application is computer assisted search of partners in online dating services. The proposed approach is based on the use of epsiv-SVMs to learn a regression function that maps low level image features onto attractiveness ratings. We present empirical results based on a dataset of images collected from a large online dating site. Our system achieved correlations of up to 0.45 (Pearson correlation) on the attractiveness predictions for individual users. We show evidence that the approach learned not just a universal sense of attraction shared by multiple users, but capitalized on the preferences of individual subjects. Our results are promising and could already be used to facilitate the personalized search of partners in online dating.</description><subject>Application software</subject><subject>Computer vision</subject><subject>Face detection</subject><subject>Facial features</subject><subject>Image databases</subject><subject>Image representation</subject><subject>Kernel</subject><subject>Linear regression</subject><subject>Machine learning</subject><subject>Principal component analysis</subject><isbn>1424421535</isbn><isbn>9781424421534</isbn><isbn>1424421543</isbn><isbn>9781424421541</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFT9tKw0AUXJGCtvYDxJf8QOJeTpLdx1JsKxQU0edy9uwJrMS07AZBv96IBedlGOYCI8StkpVS0t2vNtuXSktpK7DKGKMvxFyBBtCqBnP5L0w9E_PfoJPSSX0lljm_ywkwWQ6uRfnMKR8H7OM3h6JDitgXOI4JaYyfPHDOxSlxiJM8Djdi1mGfeXnmhXjbPLyud-X-afu4Xu1L0tDqUiuwgAQNQls7DSZ4tK4jYuelYq8oePLSeWsDm-kCNNQQtm0HU4eCWYi7v93IzIdTih-Yvg7nr-YHVIBFvQ</recordid><startdate>200809</startdate><enddate>200809</enddate><creator>Whitehill, J.</creator><creator>Movellan, J.R.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200809</creationdate><title>Personalized facial attractiveness prediction</title><author>Whitehill, J. ; Movellan, J.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2472-21484ac46a4759243dba89fcce9b01eb1cdbcb09b88de348146c6ca77f446acd3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Application software</topic><topic>Computer vision</topic><topic>Face detection</topic><topic>Facial features</topic><topic>Image databases</topic><topic>Image representation</topic><topic>Kernel</topic><topic>Linear regression</topic><topic>Machine learning</topic><topic>Principal component analysis</topic><toplevel>online_resources</toplevel><creatorcontrib>Whitehill, J.</creatorcontrib><creatorcontrib>Movellan, J.R.</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>Whitehill, J.</au><au>Movellan, J.R.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Personalized facial attractiveness prediction</atitle><btitle>2008 8th IEEE International Conference on Automatic Face & Gesture Recognition</btitle><stitle>AFGR</stitle><date>2008-09</date><risdate>2008</risdate><spage>1</spage><epage>7</epage><pages>1-7</pages><isbn>1424421535</isbn><isbn>9781424421534</isbn><eisbn>1424421543</eisbn><eisbn>9781424421541</eisbn><abstract>We present a fully automatic approach to learning the personal facial attractiveness preferences of individual users directly from example images. The target application is computer assisted search of partners in online dating services. The proposed approach is based on the use of epsiv-SVMs to learn a regression function that maps low level image features onto attractiveness ratings. We present empirical results based on a dataset of images collected from a large online dating site. Our system achieved correlations of up to 0.45 (Pearson correlation) on the attractiveness predictions for individual users. We show evidence that the approach learned not just a universal sense of attraction shared by multiple users, but capitalized on the preferences of individual subjects. Our results are promising and could already be used to facilitate the personalized search of partners in online dating.</abstract><pub>IEEE</pub><doi>10.1109/AFGR.2008.4813332</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition, 2008, p.1-7 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Application software Computer vision Face detection Facial features Image databases Image representation Kernel Linear regression Machine learning Principal component analysis |
| title | Personalized facial attractiveness prediction |
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