Facial expression recognition in dynamic sequences : An integrated approach
- Submitting institution
-
Aberystwyth University / Prifysgol Aberystwyth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6741184
- Type
- D - Journal article
- DOI
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10.1016/j.patcog.2013.09.023
- Title of journal
- Pattern Recognition
- Article number
- -
- First page
- 1271
- Volume
- 47
- Issue
- 3
- ISSN
- 0031-3203
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
8
- Research group(s)
-
-
- Citation count
- 39
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Initial work that substantially improves upon existing techniques for facial expression recognition from video sequences, by removing the need for manual thresholds or expert information that is normally required to identify the onset of a particular human facial expression. PRJ is a flagship journal in the area of Pattern Recognition. The underlying research has led to many successful applications and extensions by others (e.g., Fan and Tjahjadi, 2015; Lim et al, 2016; Ding et al. 2017; Abuzneid and ahmood, 2018; Yi et al, 2019, and Gogic et al, 2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -