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3D Face Analysis: Advances and Perspectives

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Biometric Recognition (CCBR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8833))

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Abstract

In the past decade, research on 3D face analysis has been extensively developed, and this study briefly reviews the progress achieved in data acquisition, algorithms, and experimental methodologies, for the issues of face recognition, facial expression recognition, gender and ethnicity classification, age estimation, etc., especially focusing on that after the availability of FRGC v2.0. It further points out several challenges to deal with for more efficient and reliable systems in the real world.

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Authors and Affiliations

  1. IRIP Lab, School of Comput. Sci. and Eng., Beihang Univ., Beijing, China

    Di Huang, Jia Sun, Xudong Yang, Dawei Weng & Yunhong Wang

Authors
  1. Di Huang
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  2. Jia Sun
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  3. Xudong Yang
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  4. Dawei Weng
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  5. Yunhong Wang
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Editor information

Editors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, 100190, Beijing, China

    Zhenan Sun

  2. Institute of Computing Technology, Chinese Academy of Sciences, No.6 Kexueyuan South Road, P.O. Box 2704, 100190, HaiDian, Beijing, China

    Shiguang Shan

  3. School of Information Science and Engineering, Shenyang University of Technology, No.111, Shenliao West Road, Economic and Technological Development Zone, 110870, Shenyang, China

    Haifeng Sang  & Weiqi Yuan  & 

  4. Software Engineering Institute, Tsinghua University, No. 1 Tsinghua Yuan, Haidian District, 100084, Beijing, China

    Jie Zhou

  5. School of Computer Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, 100191, Beijing, China

    Yunhong Wang

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Huang, D., Sun, J., Yang, X., Weng, D., Wang, Y. (2014). 3D Face Analysis: Advances and Perspectives. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-12484-1_1

  • Publisher Name: Springer, Cham

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