Automatic analysis of facial expressions: the state of the art. Pantic, M. and Rothkrantz, L. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(12):1424-1445, 2000.
Automatic analysis of facial expressions: the state of the art [pdf]Paper  abstract   bibtex   
Humans detect and interpret faces and facial expressions in a scene with little or no effort. Still, development of an automated system that accomplishes this task is rather difficult. There are several related problems: detection of an image segment as a face, extraction of the facial expression information, and classification of the expression (e.g., in emotion categories). A system that performs these operations accurately and in real time would form a big step in achieving a human-like interaction between man and machine. The paper surveys the past work in solving these problems. The capability of the human visual system with respect to these problems is discussed, too. It is meant to serve as an ultimate goal and a guide for determining recommendations for development of an automatic facial expression analyzer.
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 title = {Automatic analysis of facial expressions: the state of the art},
 type = {article},
 year = {2000},
 identifiers = {[object Object]},
 keywords = {Communication channels,Data mining,Emotion recognition,Face detection,Human computer interaction,Image sequence analysis,Man machine systems,Pattern recognition,Robustness,Visual system,automatic analysis,automatic facial expression analyzer,emotion categories,face recognition,facial expressions,feature extraction,human visual system,human-like interaction,image classification,image segment detection,image sequences,neural nets},
 pages = {1424-1445},
 volume = {22},
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 abstract = { Humans detect and interpret faces and facial expressions in a scene with little or no effort. Still, development of an automated system that accomplishes this task is rather difficult. There are several related problems: detection of an image segment as a face, extraction of the facial expression information, and classification of the expression (e.g., in emotion categories). A system that performs these operations accurately and in real time would form a big step in achieving a human-like interaction between man and machine. The paper surveys the past work in solving these problems. The capability of the human visual system with respect to these problems is discussed, too. It is meant to serve as an ultimate goal and a guide for determining recommendations for development of an automatic facial expression analyzer.},
 bibtype = {article},
 author = {Pantic, M. and Rothkrantz, L.J.M.},
 journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
 number = {12}
}
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