3D facial expression recognition using SIFT descriptors of automatically detected keypoints
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Starting with the publication of the BU-3DFE dataset, which provides four different intensity levels for every expression, advancements in recognizing primary expressions from 3D samples were made.
“Starting with the publication of the BU-3DFE dataset which provides four different intensity levels for every expression, advancements in recognizing primary expressions from 3D samples were made [118], [120], [124], [125], [131], [133], [217].”
From Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications (2016) · cites this paper as [120]
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Corneanu, C. A., Simon, M. O., Cohn, J. F., & Guerrero, S. E. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2515606 · Cited by 527 · see citing works
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- Authors
- Berretti, S., Ben Amor, B., Daoudi, M., & del Bimbo, A.
- Affiliations
- University of Florence (IT)
- Laboratoire d'Informatique Fondamentale de Lille (FR)
- Corresponding author
- Berretti, Stefano
- Venue
- The Visual Computer
- Published
- 2011-06-30
- Volume
- 27
- Issue
- 11
- Pages
- 1021-1036
- ISSN
- 0178-2789 (ISSN-L)
- 1432-2315
- OpenAlex
- W2162280462
- Cited by
- 138
- References
- 42
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 1 · 2023: 5 · 2022: 6 · 2021: 13 · 2020: 21 · 2019: 16 · 2018: 13 · 2017: 11 · 2016: 13 · 2015: 10 · 2014: 11 · 2013: 6 · 2012: 4
- FWCI
- 7.23
- Type
- journal article
- Language
- en
- Open access
- green
- hal.science
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- The Visual Computer (publishedVersion)
- HAL (submittedVersion, other-oa)
- Florence Research (University of Florence) (submittedVersion)
- LillOA (Université de Lille (University Of Lille)) (submittedVersion, other-oa)
- Funders
- Agence Nationale de la Recherche (ANR-07-SESU-0004)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- facial expression recognition, 3D facial expression recognition, SIFT descriptors, depth images, 3D face shape, user-independent recognition, feature selection, support vector machine, multi-class classifier, BU-3DFE
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