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Facial gesture recognition using active appearance models based on neural evolution

Published: 05 March 2012 Publication History

Abstract

Facial gesture recognition is one of the main topics in HRI. We have developed a novel algorithm who allows to detect emotional states, like happiness, sadness or emotionless. A humanoid robot is able to detect these states with a ratio of success of 83% and interact in consequence. We use Active Appearance Models (AAMs) to determinate face features and classify the emotions using neural evolution, based on neural networks and differential evolution algorithm.

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References

[1]
G. Edwards, C. Taylor, and T. Cootes. Interpreting face images using active appearance models. In Automatic Face and Gesture Recognition. Proc. Third IEEE International Conference on, pp. 300--305, 1998.
[2]
Mitra, S., and Acharya, T. Systems, Man, and Cybernetics, Part C: Applications and Reviews. IEEE Transactions on Gesture recognition, pp. 311--324 vol. 37, 2007.
[3]
Arsic, D., Schenk, J., Schuller, B. Submotions for hidden markov model based dynamic facial action recog. In Image Processing IEEE International Conference on, pp. 673--676, 2006.

Cited By

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  • (2018)A Survey of Autonomous Human Affect Detection Methods for Social Robots Engaged in Natural HRIJournal of Intelligent and Robotic Systems10.1007/s10846-015-0259-282:1(101-133)Online publication date: 30-Dec-2018
  • (2017)Human-Machine Interface Using Facial Gesture Recognitionundefined10.12794/metadc1062841Online publication date: Dec-2017

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  1. Facial gesture recognition using active appearance models based on neural evolution

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    cover image ACM Conferences
    HRI '12: Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
    March 2012
    518 pages
    ISBN:9781450310635
    DOI:10.1145/2157689

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    • IEEE-RAS: Robotics and Automation

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 05 March 2012

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    Author Tags

    1. aam
    2. gesture recognition
    3. hri
    4. humanoid
    5. neural evolution

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    HRI'12
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    HRI'12: International Conference on Human-Robot Interaction
    March 5 - 8, 2012
    Massachusetts, Boston, USA

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    Overall Acceptance Rate 268 of 1,124 submissions, 24%

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    • (2018)A Survey of Autonomous Human Affect Detection Methods for Social Robots Engaged in Natural HRIJournal of Intelligent and Robotic Systems10.1007/s10846-015-0259-282:1(101-133)Online publication date: 30-Dec-2018
    • (2017)Human-Machine Interface Using Facial Gesture Recognitionundefined10.12794/metadc1062841Online publication date: Dec-2017

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