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Asian Conference on Computer Vision

ACCV 2016: Computer Vision – ACCV 2016 Workshops pp 517–530Cite as

Expression Recognition with Ri-HOG Cascade

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10118))

Abstract

This paper presents a novel classification framework derived from AdaBoost to classify facial expressions. The proposed framework adopts rotation-reversal invariant HOG as features. The Framework is implemented through configuring the Area under ROC curve (AUC) of the weak classifier with HOG, which is a discriminative classification framework. The proposed classification framework is evaluated with two very popular and representative public databases: MMI and AFEW. As a result, it outperforms the state-of-the-arts methods.

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Author information

Authors and Affiliations

  1. RIEB, Kobe University, Kobe, 657-8501, Japan

    Jinhui Chen

  2. Graduate School of System Informatics, Kobe University, Kobe, 657-8501, Japan

    Zhaojie Luo, Tetsuya Takiguchi & Yasuo Ariki

Authors
  1. Jinhui Chen
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  2. Zhaojie Luo
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  3. Tetsuya Takiguchi
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  4. Yasuo Ariki
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Corresponding author

Correspondence to Jinhui Chen .

Editor information

Editors and Affiliations

  1. Institute of Information Science, Academia Sinica, Taipei, Taiwan

    Chu-Song Chen

  2. Tsinghua University , Beijing, China

    Jiwen Lu

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Kai-Kuang Ma

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Chen, J., Luo, Z., Takiguchi, T., Ariki, Y. (2017). Expression Recognition with Ri-HOG Cascade. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10118. Springer, Cham. https://doi.org/10.1007/978-3-319-54526-4_38

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  • DOI: https://doi.org/10.1007/978-3-319-54526-4_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54525-7

  • Online ISBN: 978-3-319-54526-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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