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UPM-3D Facial Expression Recognition Database(UPM-3DFE)

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PRICAI 2012: Trends in Artificial Intelligence (PRICAI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7458))

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Abstract

Facial expression studies have now become the central topic among computer vision community; this can be attributed to application it finds in security, human computer interaction, entertainment industries, etc. Using the state of art equipment, We Built a 3D facial expression database named UPM-3DFE database. This database contained 350 face images of 50 persons, with each posing the six universally accepted facial expressions ie; happy, sad, angry, fear, disgust and surprise. The participants are drawn from different ancestral/ethnic background. The database was evaluated using both subjective and objective analysis. We further investigated the relationship between the machine expression recognition and the human effort required to mimic the expression. The result shows a negative correlation.

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Author information

Authors and Affiliations

  1. Multimedia System Laboratory, Department of Computer and Communication Systems, Universiti Putra Malaysia, Serdang, Selangor, 43400, Malaysia

    Rabiu Habibu, Mashohor Syamsiah, Marhaban Mohammad Hamiruce & Saripan M. Iqbal

Authors
  1. Rabiu Habibu
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  2. Mashohor Syamsiah
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  3. Marhaban Mohammad Hamiruce
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  4. Saripan M. Iqbal
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Editor information

Editors and Affiliations

  1. Faculty of Environment, Society and Design, Department of Applied Computing, Lincoln University, P.O. Box 84, 7647, Christchurch, New Zealand

    Patricia Anthony

  2. School of Information Science and Technology, University of Tokyo, 7-3-1, Hongo, 113-8656, Bunkyo-ku, Tokyo, Japan

    Mitsuru Ishizuka

  3. MIMOS Berhad, Knowledge Technology, Technology Park Malaysia,, 57000, Kuala Lumpur, Malaysia

    Dickson Lukose

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© 2012 Springer-Verlag Berlin Heidelberg

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Habibu, R., Syamsiah, M., Hamiruce, M.M., Iqbal, S.M. (2012). UPM-3D Facial Expression Recognition Database(UPM-3DFE). In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_42

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  • DOI: https://doi.org/10.1007/978-3-642-32695-0_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32694-3

  • Online ISBN: 978-3-642-32695-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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