Comprehensive database for facial expression analysis

Within the past decade, significant effort has occurred in developing methods of facial expression analysis. Because most investigators have used relatively limited data sets, the generalizability of these various methods remains unknown. We describe the problem space for facial expression analysis,...

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Published in4th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2000) pp. 46 - 53
Main Authors Kanade, T., Cohn, J.F., Yingli Tian
Format Conference Proceeding
LanguageEnglish
Published IEEE 2000
Subjects
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ISBN0769505805
9780769505800
DOI10.1109/AFGR.2000.840611

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Abstract Within the past decade, significant effort has occurred in developing methods of facial expression analysis. Because most investigators have used relatively limited data sets, the generalizability of these various methods remains unknown. We describe the problem space for facial expression analysis, which includes level of description, transitions among expressions, eliciting conditions, reliability and validity of training and test data, individual differences in subjects, head orientation and scene complexity image characteristics, and relation to non-verbal behavior. We then present the CMU-Pittsburgh AU-Coded Face Expression Image Database, which currently includes 2105 digitized image sequences from 182 adult subjects of varying ethnicity, performing multiple tokens of most primary FACS action units. This database is the most comprehensive testbed to date for comparative studies of facial expression analysis.
AbstractList Within the past decade, significant effort has occurred in developing methods of facial expression analysis. Because most investigators have used relatively limited data sets, the generalizability of these various methods remains unknown. We describe the problem space for facial expression analysis, which includes level of description, transitions among expressions, eliciting conditions, reliability and validity of training and test data, individual differences in subjects, head orientation and scene complexity image characteristics, and relation to non-verbal behavior. We then present the CMU-Pittsburgh AU-Coded Face Expression Image Database, which currently includes 2105 digitized image sequences from 182 adult subjects of varying ethnicity, performing multiple tokens of most primary FACS action units. This database is the most comprehensive testbed to date for comparative studies of facial expression analysis.
Author Kanade, T.
Cohn, J.F.
Yingli Tian
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Keywords Image analysis
Image coding
Face recognition
Image processing
Image sequence
Image databank
Facies
Database
Reliability
Acquisition
Comparative study
Facial expression
Language English
License CC BY 4.0
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PublicationTitle 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2000)
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Snippet Within the past decade, significant effort has occurred in developing methods of facial expression analysis. Because most investigators have used relatively...
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StartPage 46
SubjectTerms Applied sciences
Artificial intelligence
Computer science; control theory; systems
Exact sciences and technology
Face recognition
Facial features
Gold
Head
Image analysis
Image databases
Information systems. Data bases
Layout
Memory organisation. Data processing
Pattern recognition. Digital image processing. Computational geometry
Prototypes
Robots
Software
Testing
Title Comprehensive database for facial expression analysis
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