Realtime Facial Expression Recognition from Video Sequences Using Optical Flow and Expression HMM


Jun-Chul Chun, Gi-Han Shin, Journal of Information Processing Systems Vol. 10, No. 4, pp. 55-70, Aug. 2009  


Keywords: HMM(Hidden Markov Model), optical flow, facial expression recognition, facial motion tracking
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Abstract

Vision-based Human computer interaction is an emerging field of science and industry to provide natural way to communicate with human and computer. In that sense, inferring the emotional state of the person based on the facial expression recognition is an important issue. In this paper, we present a novel approach to recognize facial expression from a sequence of input images using emotional specific HMM (Hidden Markov Model) and facial motion tracking based on optical flow. Conventionally, in the HMM which consists of basic emotional states, it is considered natural that transitions between emotions are imposed to pass through neutral state. However, in this work we propose an enhanced transition framework model which consists of transitions between each emotional state without passing through neutral state in addition to a traditional transition model. For the localization of facial features from video sequence we exploit template matching and optical flow. The facial feature displacements traced by the optical flow are used for input parameters to HMM for facial expression recognition. From the experiment, we can prove that the proposed framework can effectively recognize the facial expression in real time.


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Cite this article
[APA Style]
Chun, J. & Shin, G. (2009). Realtime Facial Expression Recognition from Video Sequences Using Optical Flow and Expression HMM. Journal of Internet Computing and Services, 10(4), 55-70.

[IEEE Style]
J. Chun and G. Shin, "Realtime Facial Expression Recognition from Video Sequences Using Optical Flow and Expression HMM," Journal of Internet Computing and Services, vol. 10, no. 4, pp. 55-70, 2009.

[ACM Style]
Jun-Chul Chun and Gi-Han Shin. 2009. Realtime Facial Expression Recognition from Video Sequences Using Optical Flow and Expression HMM. Journal of Internet Computing and Services, 10, 4, (2009), 55-70.