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A rotation-invariant facial expression recognition algorithm using localized eyes and local binary pattern

Published: 05 August 2011 Publication History

Abstract

This paper presents a rotation-invariant expression recognition algorithm that uses both localized eyes and local binary pattern (LBP) feature for SVM. This is a complete algorithm from the image input of cameras to the output of the facial expression recognition. It first localizes the eyes and then uses the localized eyes to rotate the face into upright face to achieve the rotation-invariant. It also uses the localized eyes to calculate the face box, whereas most of the existing algorithms use the face box acquired by the face detection algorithms. The experimental results show that the face boxes calculated from eye locations can improve the performance of expression recognition.

References

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M. J. Lyons, J. Budynek, and S. Akamatsu. Automatic classification of single facial images, IEEE Transactions on Pattern Analysis and Machine Intelligence, 21 (12): 1357--1362 (1999).
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C. Shan, S. Gong, and P. W. McOwan. Facial expression recognition based on Local Binary Patterns: A comprehensive study, Image and Vision Computing, vol 27: 803--816, 2009.
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X. Yu, W. Han, L. Li, K. E. Hoe, J. Yu, and G. Wang. An eye detection and localization system for natural human and robot interaction without face detection, The Conference Towards Autonomous Robotics System 2011, Sheffield, UK, 31 August- 2 September 2011.
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Cited By

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  • (2012)Spatiotemporal local orientational binary patterns for facial expression recognition from video sequences2012 9th International Conference on Fuzzy Systems and Knowledge Discovery10.1109/FSKD.2012.6234354(1421-1424)Online publication date: May-2012

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    ICIMCS '11: Proceedings of the Third International Conference on Internet Multimedia Computing and Service
    August 2011
    208 pages
    ISBN:9781450309189
    DOI:10.1145/2043674
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    • Sichuan University
    • Chinese Academy of Sciences
    • SCF: Sichuan Computer Federation
    • Southwest Jiaotong University
    • Beijing ACM SIGMM Chapter

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 05 August 2011

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    Author Tags

    1. LBP
    2. eye detection
    3. facial expression recognition
    4. rotation-invariance
    5. stereo vision

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    ICIMCS '11
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    • SCF

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    Overall Acceptance Rate 163 of 456 submissions, 36%

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    • (2012)Spatiotemporal local orientational binary patterns for facial expression recognition from video sequences2012 9th International Conference on Fuzzy Systems and Knowledge Discovery10.1109/FSKD.2012.6234354(1421-1424)Online publication date: May-2012

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