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| Micro-Expression Recognition Framework Using Time Series Analysis |
| WANG Shang-Fei,ZHANG Feng,WANG Xu-Fa |
| Computing and Communicating Software Key Laboratory of Anhui Province,College of Computer Science and Technology,University of Science and Technology of China,Hefei 230027 |
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Abstract Relying on existing exaggerated expression video database and micro-expression being regarded as former part of exaggerated expression image series, a micro-expression recognition framework based on time series analysis is presented. Firstly, five dimensions feature series, action direction and intensity rate of eyebrows, nose and mouth, are extracted by fusing optical flow field of binary videos and gray ones. Secondly, hidden Markov models are trained by adopting exaggerated expression feature series, the relationship being analyzed between feature series and exaggerated expressions. Finally, these models are used to predict the variety trend of micro-expressions and recognize them and boosting algorithm is employed to increase recognition accuracy. The effectiveness of the approach is evaluated on Cohn Kanade facial expression database and a preferable experiment result is obtained.
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Received: 08 December 2008
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2010, Vol. 23 
