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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Monwar, Md.M. Rezaei, S. |
| Copyright Year | 2006 |
| Description | Author affiliation: Comput. Sci., Northern British Columbia Univ., Prince George, BC (Monwar, Md.M.; Rezaei, S.) |
| Abstract | Facial expressions are a key index of emotion. To make use of the information afforded by facial expression for emotion science and clinical practice, reliable, valid, and efficient methods of measurement are critical. Enabling computer systems to recognize facial expressions and infer emotions from them is a challenging research topic. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector and facial feature tracker for face detection and feature extraction respectively. The face detector uses skin color modeling approach. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to the artificial neural network which uses standard error backpropagation algorithm for classification of painful and painless faces |
| Starting Page | 28 |
| Ending Page | 33 |
| File Size | 314106 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780397533 |
| DOI | 10.1109/ISSPIT.2006.270764 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-08-27 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pain Artificial neural networks Face detection Face recognition Detectors Computer network reliability Emotion recognition Humans Facial features Feature extraction error back-propagation Pain recognition skin color model location features shape features |
| Content Type | Text |
| Resource Type | Article |
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