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Asian Conference on Computer Vision

ACCV 2012: Computer Vision – ACCV 2012 pp 565–576Cite as

Face Recognition after Plastic Surgery: A Comprehensive Study

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7725))

Abstract

It has been observed that many face recognition algorithms fail to recognize faces after plastic surgery, which thus poses a new challenge to automatic face recognition. This paper first gives a comprehensive study on Face Recognition After Plastic Surgery (FRAPS), with careful analysis of the effects of plastic surgery on face appearance and its challenges to face recognition. Then, to address FRAPS problem, an ensemble of Gabor Patch classifiers via Rank-Order list Fusion (GPROF) is proposed, inspired by the assumption of the interior consistency of face components in terms of identity. On the face database of plastic surgery, GPROF achieves much higher face identification rate than the best known results in the literature. Furthermore, with our impressive results, we suggest that plastic surgery detection should be paid more attend to. To address this problem, a partial matching based plastic surgery detection algorithm is proposed, aiming to detect four distinct types of surgery, i.e., the eyelid surgery, nose surgery, forehead surgery and face lift surgery. Our experimental results demonstrate that plastic surgery detection is a nontrivial task, and thus deserves more research efforts.

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Author information

Authors and Affiliations

  1. Key Lab of Intelligent Information Processing, Chinese Academy of Sciences (CAS), Beijing, 100190, China

    Xin Liu, Shiguang Shan & Xilin Chen

  2. Institute of Computing Technology, CAS, Beijing, 100190, China

    Xin Liu, Shiguang Shan & Xilin Chen

  3. University of Chinese Academy of Sciences, Beijing, 100049, China

    Xin Liu

Authors
  1. Xin Liu
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  2. Shiguang Shan
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  3. Xilin Chen
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, 151-744, Seoul, Korea

    Kyoung Mu Lee

  2. Microsoft Research Asia, No. 5, Danling st., Haidian district, 100080, Beijing, P.R. China

    Yasuyuki Matsushita

  3. School of Interactive Computing, Georgia Institute of Technology, 801 Atlantic Drive, CCB 315, 30332, Atlanta, GA, USA

    James M. Rehg

  4. Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Zhong Quan Cun East Road 95, Haidian District, 100 190, Beijing, P.R. China

    Zhanyi Hu

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© 2013 Springer-Verlag Berlin Heidelberg

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Liu, X., Shan, S., Chen, X. (2013). Face Recognition after Plastic Surgery: A Comprehensive Study. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7725. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37444-9_44

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  • DOI: https://doi.org/10.1007/978-3-642-37444-9_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37443-2

  • Online ISBN: 978-3-642-37444-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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