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Conversational Interaction Recognition Based on Bodily and Facial Movement

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Image Analysis and Recognition (ICIAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8814))

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Abstract

We examine whether 3D pose and face features can be used to both learn and recognize different conversational interactions. We believe this to be among the first work devoted to this subject and show that this task is indeed possible with a promising degree of accuracy using both features derived from pose and face. To extract 3D pose we use the Kinect Sensor, and we use a combined local and global model to extract face features from normal RGB cameras. We show that whilst both of these features are contaminated with noises. They can still be used to effectively train classifiers. The differences in interaction among different scenarios in our data set are extremely subtle. Both generative and discriminative methods are investigated, and a subject specific supervised learning approach is employed to classify the testing sequences to seven different conversational scenarios.

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Authors and Affiliations

  1. Department of Computer Science, Swansea University, Swansea, UK

    Jingjing Deng, Xianghua Xie & Shangming Zhou

Authors
  1. Jingjing Deng
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  2. Xianghua Xie
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  3. Shangming Zhou
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Corresponding author

Correspondence to Xianghua Xie .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Aurélio Campilho

  2. Dept. of Electrical and Computer Eng., University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

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Deng, J., Xie, X., Zhou, S. (2014). Conversational Interaction Recognition Based on Bodily and Facial Movement. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8814. Springer, Cham. https://doi.org/10.1007/978-3-319-11758-4_26

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  • DOI: https://doi.org/10.1007/978-3-319-11758-4_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11757-7

  • Online ISBN: 978-3-319-11758-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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