Real Time Facial Expression Recognition Using Local Binary Patterns and Linear Programming
In this paper, a fully automatic, real-time system is proposed to recognize seven basic facial expressions (angry, disgust, fear, happiness, neutral, sadness and surprise). First, faces are located and normalized based on an illumination insensitive skin model and face segmentation; then, the Local...
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| creator | Feng, Xiaoyi Cui, Jie Pietikäinen, Matti Hadid, Abdenour |
| description | In this paper, a fully automatic, real-time system is proposed to recognize seven basic facial expressions (angry, disgust, fear, happiness, neutral, sadness and surprise). First, faces are located and normalized based on an illumination insensitive skin model and face segmentation; then, the Local Binary Patterns (LBP) techniques, which are invariant to monotonic grey level changes, are used for facial feature extraction; finally, the Linear Programming (LP) technique is employed to classify seven facial expressions. Theoretical analysis and experimental results show that the proposed system performs well in some degree of illumination changes and head rotations. |
| doi_str_mv | 10.1007/11579427_33 |
| format | Conference Proceeding |
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First, faces are located and normalized based on an illumination insensitive skin model and face segmentation; then, the Local Binary Patterns (LBP) techniques, which are invariant to monotonic grey level changes, are used for facial feature extraction; finally, the Linear Programming (LP) technique is employed to classify seven facial expressions. Theoretical analysis and experimental results show that the proposed system performs well in some degree of illumination changes and head rotations.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540298960</identifier><identifier>ISBN: 3540298967</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 3540316531</identifier><identifier>EISBN: 9783540316534</identifier><identifier>DOI: 10.1007/11579427_33</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Exact sciences and technology ; Expression Recognition ; Facial Expression ; Facial Expression Recognition ; Facial Feature ; Local Binary Pattern ; Pattern recognition. Digital image processing. 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First, faces are located and normalized based on an illumination insensitive skin model and face segmentation; then, the Local Binary Patterns (LBP) techniques, which are invariant to monotonic grey level changes, are used for facial feature extraction; finally, the Linear Programming (LP) technique is employed to classify seven facial expressions. Theoretical analysis and experimental results show that the proposed system performs well in some degree of illumination changes and head rotations.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Expression Recognition</subject><subject>Facial Expression</subject><subject>Facial Expression Recognition</subject><subject>Facial Feature</subject><subject>Local Binary Pattern</subject><subject>Pattern recognition. Digital image processing. 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Computational geometry</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Feng, Xiaoyi</creatorcontrib><creatorcontrib>Cui, Jie</creatorcontrib><creatorcontrib>Pietikäinen, Matti</creatorcontrib><creatorcontrib>Hadid, Abdenour</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Feng, Xiaoyi</au><au>Cui, Jie</au><au>Pietikäinen, Matti</au><au>Hadid, Abdenour</au><au>Terashima-Marín, Hugo</au><au>de Albornoz, Álvaro</au><au>Gelbukh, Alexander</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Real Time Facial Expression Recognition Using Local Binary Patterns and Linear Programming</atitle><btitle>Lecture notes in computer science</btitle><date>2005</date><risdate>2005</risdate><spage>328</spage><epage>336</epage><pages>328-336</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540298960</isbn><isbn>3540298967</isbn><eisbn>3540316531</eisbn><eisbn>9783540316534</eisbn><abstract>In this paper, a fully automatic, real-time system is proposed to recognize seven basic facial expressions (angry, disgust, fear, happiness, neutral, sadness and surprise). First, faces are located and normalized based on an illumination insensitive skin model and face segmentation; then, the Local Binary Patterns (LBP) techniques, which are invariant to monotonic grey level changes, are used for facial feature extraction; finally, the Linear Programming (LP) technique is employed to classify seven facial expressions. Theoretical analysis and experimental results show that the proposed system performs well in some degree of illumination changes and head rotations.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/11579427_33</doi><tpages>9</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 2005, p.328-336 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_17416086 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Expression Recognition Facial Expression Facial Expression Recognition Facial Feature Local Binary Pattern Pattern recognition. Digital image processing. Computational geometry |
| title | Real Time Facial Expression Recognition Using Local Binary Patterns and Linear Programming |
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