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.