2 February 2009 Support vector machine for automatic pain recognition
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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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Md Maruf Monwar, Md Maruf Monwar, Siamak Rezaei, Siamak Rezaei, } "Support vector machine for automatic pain recognition", Proc. SPIE 7246, Computational Imaging VII, 724613 (2 February 2009); doi: 10.1117/12.806143; https://doi.org/10.1117/12.806143


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