Detection, tracking, and classification of action units in facial expression
By J. Lien, Takeo Kanade, Jeffrey F. Cohn, Ching-Chung Li. Robotics Auton. Syst., 2000
359 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/973f8361c4ca2eda88e4fa37e6dcdcbe074b01dd
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Maja Pantic
- Michel François Valstar
- Jeffrey F. Cohn
- Qiang Ji
- Brais Martínez
- Bihan Jiang
- Yan Tong
- Wenhui Liao
In Experimental and Cognitive Psychology
- Maja Pantic
- Michel François Valstar
- Jeffrey F. Cohn
- Qiang Ji
- Bihan Jiang
- Brais Martínez
- Yan Tong
- Wenhui Liao
Citations in the corpus
- Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships (2007, methodology): “The local methods [4], [9], [10], [3], [11], [12], [13], [14], [15], [16] focus on the facial features locally.”
- Automatic Analysis of Facial Actions: A Survey (2019, methodology): “flow (OF) were considered as an alternative to d images in early works ([53], [101]).”
- Recognizing Action Units for Facial Expression Analysis (2001, background): “Human emotions and intentions are more often communicated by changes in one or a few discrete facial features.”
- Active and dynamic information fusion for facial expression understanding from image sequences (2005, background): “The works in [36] and [22] focus on recognizing facial AUs rather than facial expressions.”
- Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines (2007, neutral): “HMMs are also used in [28].”