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Proceedings Paper

Support vector machine for automatic pain recognition
Author(s): Md Maruf Monwar; Siamak Rezaei
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Paper Abstract

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. 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 which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

Paper Details

Date Published: 3 February 2009
PDF: 8 pages
Proc. SPIE 7246, Computational Imaging VII, 724613 (3 February 2009); doi: 10.1117/12.806143
Show Author Affiliations
Md Maruf Monwar, Univ. of Calgary (Canada)
Siamak Rezaei, Univ. of Northern British Columbia (Canada)

Published in SPIE Proceedings Vol. 7246:
Computational Imaging VII
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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