Automatic analysis of facial actions: a survey
As one of the most comprehensive and objective ways to describe facial expressions, the Facial Action Coding System (FACS) has recently received significant attention. Over the past 30 years, extensive research has been conducted by psychologists and neuroscientists on various aspects of facial expr...
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| Format: | Article |
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Institute of Electrical and Electronics Engineers (IEEE)
2017
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| Online Access: | https://eprints.nottingham.ac.uk/44740/ |
| _version_ | 1848796987777875968 |
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| author | Martinez, Brais Valstar, Michel F. Jiang, Bihan Pantic, Maja |
| author_facet | Martinez, Brais Valstar, Michel F. Jiang, Bihan Pantic, Maja |
| author_sort | Martinez, Brais |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | As one of the most comprehensive and objective ways to describe facial expressions, the Facial Action Coding System (FACS) has recently received significant attention. Over the past 30 years, extensive research has been conducted by psychologists and neuroscientists on various aspects of facial expression analysis using FACS. Automating FACS coding would make this research faster and more widely applicable, opening up new avenues to understanding how we communicate through facial expressions. Such an automated process can also potentially increase the reliability, precision and temporal resolution of coding. This paper provides a comprehensive survey of research into machine analysis of facial actions. We systematically review all components of such systems: pre-processing, feature extraction and machine coding of facial actions. In addition, the existing FACS-coded facial expression databases are summarised. Finally, challenges that have to be addressed to make automatic facial action analysis applicable in real-life situations are extensively discussed. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into the future of machine recognition of facial actions: what are the challenges and opportunities that researchers in the field face. |
| first_indexed | 2025-11-14T19:56:43Z |
| format | Article |
| id | nottingham-44740 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:56:43Z |
| publishDate | 2017 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-447402020-05-04T18:48:42Z https://eprints.nottingham.ac.uk/44740/ Automatic analysis of facial actions: a survey Martinez, Brais Valstar, Michel F. Jiang, Bihan Pantic, Maja As one of the most comprehensive and objective ways to describe facial expressions, the Facial Action Coding System (FACS) has recently received significant attention. Over the past 30 years, extensive research has been conducted by psychologists and neuroscientists on various aspects of facial expression analysis using FACS. Automating FACS coding would make this research faster and more widely applicable, opening up new avenues to understanding how we communicate through facial expressions. Such an automated process can also potentially increase the reliability, precision and temporal resolution of coding. This paper provides a comprehensive survey of research into machine analysis of facial actions. We systematically review all components of such systems: pre-processing, feature extraction and machine coding of facial actions. In addition, the existing FACS-coded facial expression databases are summarised. Finally, challenges that have to be addressed to make automatic facial action analysis applicable in real-life situations are extensively discussed. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into the future of machine recognition of facial actions: what are the challenges and opportunities that researchers in the field face. Institute of Electrical and Electronics Engineers (IEEE) 2017-06-03 Article PeerReviewed Martinez, Brais, Valstar, Michel F., Jiang, Bihan and Pantic, Maja (2017) Automatic analysis of facial actions: a survey. IEEE Transactions on Affective Computing . ISSN 1949-3045 (In Press) Action Unit analysis facial expression recognition survey doi:10.1109/TAFFC.2017.2731763 doi:10.1109/TAFFC.2017.2731763 |
| spellingShingle | Action Unit analysis facial expression recognition survey Martinez, Brais Valstar, Michel F. Jiang, Bihan Pantic, Maja Automatic analysis of facial actions: a survey |
| title | Automatic analysis of facial actions: a survey |
| title_full | Automatic analysis of facial actions: a survey |
| title_fullStr | Automatic analysis of facial actions: a survey |
| title_full_unstemmed | Automatic analysis of facial actions: a survey |
| title_short | Automatic analysis of facial actions: a survey |
| title_sort | automatic analysis of facial actions: a survey |
| topic | Action Unit analysis facial expression recognition survey |
| url | https://eprints.nottingham.ac.uk/44740/ https://eprints.nottingham.ac.uk/44740/ |