SAMM: A Spontaneous Micro-Facial Movement Dataset
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2333
- Type
- D - Journal article
- DOI
-
10.1109/TAFFC.2016.2573832
- Title of journal
- IEEE Transactions on Affective Computing
- Article number
- -
- First page
- 116
- Volume
- 9
- Issue
- 1
- ISSN
- 1949-3045
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2016
- URL
-
https://e-space.mmu.ac.uk/617069/
- 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
- Yes
- Number of additional authors
-
4
- Research group(s)
-
B - Human Centred-Computing
- Citation count
- 60
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents the world’s first spontaneous micro-facial movement dataset. It was created with the Emotional Intelligence Academy and uses a novel micro-movement detection method. The dataset has set a new standard and formed the basis of the Facial Micro-Expressions Grand Challenges (2018 – 2020), in conjunction with the International Conference on Automatic Face and Gesture Recognition. The authors were invited to present at several international talks (including the Asian Conference on Computer Vision) and offered a Visiting Professorship in China. It led to 10 international joint papers with researchers from China, Malaysia and Oulu and 2 grant submissions.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
