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
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.
[1] Zeng Zhihong, Pantic M, Roisman G I, et al. A Survey of Affect Recognition Methods: Audio,Visual, and Spontaneous Expressions. IEEE Trans on Pattern Analysis and Machine Intelligence, 2009, 31(1): 39-58 [2] Fasel B, Luettin J. Automatic Facial Expression Analysis: A Survey. Pattern Recognition, 2003, 36(1): 259-275 [3] He Lianghua, Zou Cairong, Bao Yongqiang, et al. The Research Advance of Facial Expression Recognition. Journal of Circuits and Systems, 2005, 10(1): 70-75 (in Chinese) (何良华,邹采荣,包永强,等.人脸面部表情识别的研究进展.电路与系统学报, 2005, 10(1): 70-75) [4] Wang Zhiliang, Liu Fang, Wang Li. Survey of Facial Expression Recognition Based on Computer Vision. Computer Engineering, 2006, 32(11): 231-233 (in Chinese) (王志良,刘 芳,王 莉.基于计算机视觉的表情识别技术综述.计算机工程, 2006, 32(11): 231-233) [5] Liu Xiaomin, Tan Huachun, Zhang Yujin. New Research Advances in Facial Expression Recognition. Journal of Image and Graphics, 2006, 11(10): 1359-1368 (in Chinese) (刘晓旻,谭华春,章毓晋.人脸表情识别研究的新进展.中国图象图形学报, 2006, 11(10): 1359-1368) [6] Pantic M, Rothkrantz L. Expert System for Automatic Analysis of Facial Expression. Image Vision Computing, 2000, 18(11): 881-905 [7] Zhen Wen, Huang T S. Capturing Subtle Facial Motions in 3D Face Tracking // Proc of the 9th IEEE International Conference on Computer Vision. Nice, France, 2003, Ⅱ: 1343-1350 [8] Horn B K P, Shunck B G. Determining Optical Flow. Artificial Intelligence, 1981, 17: 185-203 [9] Cappé O, Moulines E, Ryden T. Inference in Hidden Markov Models. New York, USA: Springer, 2005 [10] Freund Y. Boosting a Weak Learning Algorithm by Majority. Information and Computation, 1995, 121(2): 256-285
2010, Vol. 23 
