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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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
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