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Facial Expression Recognition Using Pyramid Local Phase Quantization Descriptor

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Knowledge and Systems Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 326))

Abstract

Facial expression recognition is a challenging and interesting problem. It has many potential and important applications in data-driven animation, human computer interaction (HCI), social robots, deceit detection and behavior monitoring. In this paper, we present the novel descriptors Pyramid local phase quantization (PLPQ). The effective of our proposed descriptor is evaluated by facial expressions recognition very efficiently and with high accuracy. On the other hand, the proposed framework extracts texture features in a pyramidal fashion only from the perceptual salient region of the face thereby our proposed framework achieved reduction in computation time of feature extraction and improved accuracy. There with the proposed framework achieved accuracy of 96.7% on extended Cohn-Kanade (CK+) posed facial expression database for six basic emotions and exceed the state-of-theart methods for expression recognition using texture features.

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Author information

Authors and Affiliations

  1. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Viet Nam

    Anh Vo

  2. Faculty of Information Technology, University of Science, Ho Chi Minh City, Viet Nam

    Ngoc Quoc Ly

Authors
  1. Anh Vo
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  2. Ngoc Quoc Ly
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Corresponding author

Correspondence to Anh Vo .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Viet-Ha Nguyen

  2. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Anh-Cuong Le

  3. School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

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© 2015 Springer International Publishing Switzerland

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Vo, A., Ly, N.Q. (2015). Facial Expression Recognition Using Pyramid Local Phase Quantization Descriptor. In: Nguyen, VH., Le, AC., Huynh, VN. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-11680-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-11680-8_9

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11679-2

  • Online ISBN: 978-3-319-11680-8

  • eBook Packages: EngineeringEngineering (R0)

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