Abstract
This paper proposes a case-based automatic facial AU recognition approach using IGA, which embeds human’s ability to compare into target system. To obtain AU codes of a new facial image, IGA is applied to retrieve a match instance based on users’ evaluation, from the case base. Then the solution suggested by the matching case is used as the AU codes to the new facial image. The effectiveness of our approach is evaluated by 16 standard facial images collected under controlled imaging conditions and 10 un-standard images collected under spontaneous conditions using the Cohn _ Kanade Facial Expression Database as case base. To standard images, a recognition rate of 77.5% is achieved on single AUs, and a similarity rate of 82.8% is obtained on AU combinations. To un-standard images, a recognition rate of 82.8% is achieved on single AUs, and a similarity rate of 93.1% is obtained on AU combinations.
This paper is supported by NSFC project (NO. 60401004).
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References
Ekman, P., Froesem, W.: Facial action coding system: a technique for the measurement of facial movement. Consulting Psychologists Press, Palo Alto (1978)
Bartlett, M.S., Hager, J.C., Ekman, P., Sejnowski, T.J.: Measuring facial expression by computer image analysis. Psychopshysiology 36, 253–263 (1999)
Donato, G., Bartlett, M.S., Hager, J.C., Ekman, P., Sejnowski, T.J.: Classifying facial actions. IEEE trans. on Analysis and Machine Intelligence 21, 974–989 (1999)
Cohn, J.F., Zlochower, A.J., Lien, J., Kanade, T.: Automated face analysis by feature point tracking has high concurrent validity with manual FACS coding. Psychophysiology 36, 35–43 (1999)
Tian, Y.L., Kanade, T., Cohn, J.F.: Recognizing action units for facial expression analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence 23(2), 97–115 (2001)
Kapoor, A.: Automatic facial action analysis. Master thesis MIT (2002)
Pantic, M., Rothkrantz, L.J.M.: Facial action recognition for facial expression analysis from static face images. IEEE Transactions on Systems, Man, and Cybernetics - Part B 34(3), 1449–1461 (2004)
Kanade, T., Cohn, J.F., Tian, Y.L.: Comprehensive database for facial expression analysis. In: Preceedings of the Fourth IEEE International Conference on Automatic Facial and Gesture Recognition (2000)
Takagi, H.: Interactive evolutionary computation: fusion of the capacities of EC optimization and human evaluation. Proceedings of the IEEE 89(9), 1275–1296 (2001)
Smith, J.R.: Designing biomorphs with an interactive genetic algorithm. In: Proceedings of the Fourth International Conference on Genetic Algorithms, pp. 535–538 (1991)
Lutton, E., Jacques, P.G., Vehel, L.: An interactive EA for multifractal bayesian denoising. In: EvoWorkshops 2005, pp. 274–283 (2005)
Wang, S.F.: Interactive Kansei-oriented image retrieval. In: Liu, J., Yuen, P.C., Li, C.-H., Ng, J., Ishida, T. (eds.) AMT 2001. LNCS, vol. 2252, pp. 377–388. Springer, Heidelberg (2002)
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Wang, S., Xue, J. (2005). Case-Based Facial Action Units Recognition Using Interactive Genetic Algorithm. In: Tao, J., Tan, T., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2005. Lecture Notes in Computer Science, vol 3784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573548_11
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DOI: https://doi.org/10.1007/11573548_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29621-8
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