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Advances in Signal Processing and Intelligent Recognition Systems pp 63–73Cite as

Emotion Recognition from 3D Images with Non-Frontal View Using Geometric Approach

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 425))

Abstract

Over the last decade emotion recognition has gained prominence for its applications in the field of Human Robot Interaction (HRI), intelligent vehicle, patient health monitoring, etc. The challenges in emotion recognition from non-frontal images, motivates researchers to explore further. In this paper, we have proposed a method based on geometric features, considering 4 yaw angles (0˚, +15˚, +30˚, +45˚) from BU-3DFE database. The novelty in our proposed work lies in identifying the most appropriate set of feature points and formation of feature vector using two different approaches. Neural network is used for classification. Among the 6 basic emotions four emotions i.e., anger, happy, sad and surprise are considered. The results are encouraging. The proposed method may be implemented for combination of pitch and yaw angles in future.

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Author information

Authors and Affiliations

  1. Amrita Robotic Research Centre, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, 560 035, Karnataka, India

    D. KrishnaSri, P. Suja & Shikha Tripathi

Authors
  1. D. KrishnaSri
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  2. P. Suja
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  3. Shikha Tripathi
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Corresponding author

Correspondence to D. KrishnaSri .

Editor information

Editors and Affiliations

  1. and Management – Kerala (IIITM-K), Indian Inst. of Information Technology, Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Sanghamitra Bandyopadhyay

  3. Department of Electrical, Ryerson University, Toronto, Ontario, Canada

    Sri Krishnan

  4. Providence University, Taichung, Taiwan

    Kuan-Ching Li

  5. Computer Engineering Department, Vladimir State University, Vladimir Region, Russia

    Sergey Mosin

  6. School of Electrical, Nanyang Technological University, Singapore, Singapore

    Maode Ma

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© 2016 Springer International Publishing Switzerland

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KrishnaSri, D., Suja, P., Tripathi, S. (2016). Emotion Recognition from 3D Images with Non-Frontal View Using Geometric Approach. In: Thampi, S., Bandyopadhyay, S., Krishnan, S., Li, KC., Mosin, S., Ma, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-319-28658-7_6

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  • DOI: https://doi.org/10.1007/978-3-319-28658-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28656-3

  • Online ISBN: 978-3-319-28658-7

  • eBook Packages: EngineeringEngineering (R0)

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