Department of Information Management, Hunan University of Finance and Economics, 410205, China

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Abstract—Human activity analysis and expressions recognition play a central role in pervasive health care. Expressions recognition is an active research field in computer vision. In this paper, We propose an approach for automatically recognizing the pain expression from video sequences, in which pain is categorized into four levels, including “no-pain”, “slight pain”, “moderate pain” and “severe pain”. First of all, each frame in video sequences is represented as a “word” by extracting facial velocity information, which is used to charaterize pain expression. Then boosting fuzzy classification algorithm is used for pain expression recognition. The algorithm can automatically categorize and recognize the human pain expression which is contained in the video. Finally we test our algorithm on a pain expression dataset built by ourselves. Experiment results show that the average recognition accuracy is over 91%, which validates its effectiveness. Our results are significantly better than three state-of-the-art approaches for pain expression recognition on the same data.

Index Terms—Pain recognition, Motion feature, Bag of Words, Boosting algorithm

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Cite: Shaoping Zhu, "Pain Expression Recognition Based on Fuzzy Classification Approach," Journal of Computers vol. 9, no. 8, pp. 1975-1982, 2014.