The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Real Time Face Detection and Facial Expression Recognition: Development and Applications to Human Computer Interaction.
Abstract
Computer animated agents and robots bring a social dimension to human computer interaction and force us to think in new ways about how computers could be used in daily life. Face to face communication is a real-time process operating at a a time scale in the order of 40 milliseconds. The level of uncertainty at this time scale is considerable, making it necessary for humans and machines to rely on sensory rich perceptual primitives rather than slow symbolic inference processes. In this paper we present progress on one such perceptual primitive. The system automatically detects frontal faces in the video stream and codes them with respect to 7 dimensions in real time: neutral, anger, disgust, fear, joy, sadness, surprise. The face finder employs a cascade of feature detectors trained with boosting techniques [15, 2]. The expression recognizer receives image patches located by the face detector. A Gabor representation of the patch is formed and then processed by a bank of SVM classifiers. A novel combination of Adaboost and SVM's enhances performance. The system was tested on the Cohn-Kanade dataset of posed facial expressions [6]. The generalization performance to new subjects for a 7- way forced choice correct. Most interestingly the outputs of the classifier change smoothly as a function of time, providing a potentially valuable representation to code facial expression dynamics in a fully automatic and unobtrusive manner. The system has been deployed on a wide variety of platforms including Sony's Aibo pet robot, ATR's RoboVie, and CU animator, and is currently being evaluated for applications including automatic reading tutors, assessment of human-robot interaction.
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Cites
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Neural network-based face detection
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Automatic analysis of facial expressions: the state of the art
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Robovie: an interactive humanoid robot
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Cited by
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
Zhao, G., & Pietikainen, M. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1110 · Cited by 2,846
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Shan, C., Gong, S., & McOwan, P. W. (2009) · Image and Vision Computing · doi:10.1016/j.imavis.2008.08.005 · Cited by 2,300
Kotsia, I., & Pitas, I. (2007) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.884954 · Cited by 687
Automatic Recognition of Facial Actions in Spontaneous Expressions
Bartlett, M. S., Littlewort, G. C., Frank, M. G., Lainscsek, C., Fasel, I. R., & Movellan, J. R. (2006) · Journal of Multimedia · doi:10.4304/jmm.1.6.22-35 · Cited by 468
Self-citationFace Expression Recognition and Analysis: The State of the Art
Bettadapura, V. (2012) · arXiv · doi:10.48550/arxiv.1203.6722 · Cited by 336
Metadata
- Authors
- Bartlett, M. S., Littlewort, G., Fasel, I., & Movellan, J. R.
- Venue
- 2003 Conference on Computer Vision and Pattern Recognition Workshop
- Publisher
- IEEE
- Published
- 2003-06
- Pages
- 53-53
- OpenAlex
- W2115941714
- Cited by
- 573
- References
- 4
- FWCI
- 29.22
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Bartlett, M. S., Littlewort, G., Fasel, I., & Movellan, J. R. (2003). Real Time Face Detection and Facial Expression Recognition: Development and Applications to Human Computer Interaction. 2003 Conference on Computer Vision and Pattern Recognition Workshop. https://doi.org/10.1109/cvprw.2003.10057
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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