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An Efficient Technique for Facial Expression Recognition Using Multistage Hidden Markov Model

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Soft Computing: Theories and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 742))

Abstract

Partition-based feature extraction is widely used in the pattern recognition and computer vision. This method is robust to some changes like occlusion, background, etc. In this paper, partition-based technique is used for feature extraction and extension of HMM is used as a classifier. The new introduced multistage HMM consists of two layers. In which bottom layer represents the atomic expression made by eyes, nose, and lips. Further upper layer represents the combination of these atomic expressions such as smile, fear, etc. Six basic facial expressions are recognized, i.e., anger, disgust, fear, joy, sadness, and surprise. Experimental result shows that proposed system performs better than normal HMM and has the overall accuracy of 85% using JAFFE database.

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Author information

Authors and Affiliations

  1. AKTU, Lucknow, India

    Mayur Rahul

  2. Department of Computer Applications, UIET, CSJMU, Kanpur, India

    Pushpa Mamoria

  3. Department of Computer Science & Engineering, HBTU, Kanpur, India

    Narendra Kohli

  4. Department of IT, UIET, CSJMU, Kanpur, India

    Rashi Agrawal

Authors
  1. Mayur Rahul
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  2. Pushpa Mamoria
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  3. Narendra Kohli
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  4. Rashi Agrawal
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Corresponding author

Correspondence to Mayur Rahul .

Editor information

Editors and Affiliations

  1. Department of Physics, Amity School of Applied Sciences, Amity University Rajasthan, Jaipur, Rajasthan, India

    Kanad Ray

  2. Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Rajasthan, Jaipur, Rajasthan, India

    Tarun K. Sharma

  3. Department of Electronics and Communication Engineering, SEEC, Manipal University Jaipur, Jaipur, Rajasthan, India

    Sanyog Rawat

  4. Institute of Basic Science, Bundelkhand University, Jhansi, Uttar Pradesh, India

    R. K. Saini

  5. Advanced Key Technologies Division, Nano Characterization Unit, Surface Characterization Group, National Institute for Materials Science, Tsukuba, Ibaraki, Japan

    Anirban Bandyopadhyay

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Rahul, M., Mamoria, P., Kohli, N., Agrawal, R. (2019). An Efficient Technique for Facial Expression Recognition Using Multistage Hidden Markov Model. In: Ray, K., Sharma, T., Rawat, S., Saini, R., Bandyopadhyay, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 742. Springer, Singapore. https://doi.org/10.1007/978-981-13-0589-4_4

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