Expert system for automatic analysis of facial expressions
By Maja Pantic, Léon J. M. Rothkrantz. Image and Vision Computing, 2000
488 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/20f1650f5c2f686bf2e0eef4ffec6e0bc37b7f55
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
- Shaogang Gong
- Peter W. McOwan
- Caifeng Shan
- Jeffrey F. Cohn
- Peter Robinson
- Ioannis Patras
- Irene Kotsia
In Experimental and Cognitive Psychology
- Maja Pantic
- Peter W. McOwan
- Caifeng Shan
- Shaogang Gong
- Jeffrey F. Cohn
- Irene Kotsia
- Peter Robinson
- Ioannis Pitas
Citations in the corpus
- Observer-based measurement of facial expression with the Facial Action Coding System. (2007, unknown): “…1998; Rinn, 1984, 1991), computer vision (Bartlett, 204 Emotion Assessment Ekman, Hager, & Sejnowski, 1999; Cohn, Zlochower, Lien, & Kanade, 1999; Pantic & Rothkrantz, 2000; Tian, Cohn, & Kanade, 2005), computer graphics and animation (Breidt, Wallraven, Cunningham, & Buelthoff, 2003; Parke &…”
- Measuring Facial Action (2008, background): “…University / University of Pittsburgh Cohn et al. 1999 Lien et al. 2000 Tian et al. 2001, 2002 Cohn et al. 2004a Delft University of Technology Pantic & Rothkrantz 2000b, 2003, 2004 Valstar et al. 2004 Institut Dalle Molle d’Intelligence ArtiWcielle Fasel & Luettin 2000 University of…”
- Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines (2007, methodology): “These FAUs are combined in order to create the rules responsible for the formation of facial expressions as proposed in [3].”
- Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences (2006, background): “The majority of this previous work concerns automatic AU recognition in static face images [7], [25].”
- Toward an affect-sensitive multimodal human-computer interaction (2003, background): “Automatic analyzers of sensed nonverbal affective cues must at least realize quantified classification into multiple-emotion categories, as proposed, for example, in [32], [53], [84], and [124] for automatic facial affect analysis and in [2] and [74] for automatic vocal affect analysis.”
- Real-Time Inference of Complex Mental States from Facial Expressions and Head Gestures (2004, background): “Features based on facial point displacements are also common and and have shown validity when compared to manual FACS coding (e.g. Cohn et al. [7], the authors [15], and Pantic and Rothkrantz [17]).”
- Facial expression recognition based on Local Binary Patterns: A comprehensive study (2009, methodology): “Facial geometry analysis has been widely exploited in facial representation [9,10,16,17,24], where shapes and locations of facial components are extracted to represent the face geometry.”