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Gabor Filter and ICA-Based Facial Expression Recognition Using Two-Layered Hidden Markov Model

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Advances in Computational Intelligence and Communication Technology


This paper introduces the framework based on the extraction of features using Gabor filters and modified hidden Markov model for classification. The three regions of interest (nose, mouth and eyes) are extracted using Gabor filters and dimensions are reduced by independent component analysis. Then these reduced dimensions are input to our two-layered HMM for training and testing. Seven facial expressions are recognized using publicly available JAFFE dataset. Experimental data shows the efficient and robust nature of our framework and shows its uniqueness on comparing it with other existing available methods.

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Japanese Female Facial Expression (JAFFE) is publicly available datasets. It is available free of charge from Web site The database was planned and assembled by Michael Lyons, Miyuki Kamachi and Jiro Gyoba.

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Correspondence to Puneet Kumar Goyal .

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Rahul, M., Shukla, R., Goyal, P.K., Siddiqui, Z.A., Yadav, V. (2021). Gabor Filter and ICA-Based Facial Expression Recognition Using Two-Layered Hidden Markov Model. In: Gao, XZ., Tiwari, S., Trivedi, M., Mishra, K. (eds) Advances in Computational Intelligence and Communication Technology. Advances in Intelligent Systems and Computing, vol 1086. Springer, Singapore.

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