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Multiscale overlapping blocks binarized statistical image features descriptor with flip-free distance for face verification in the wild

  • Tianyu Geng
  • Menglong Yang
  • Zhisheng You
  • Ying Cai
  • Feihu Huang
Original Article
  • 104 Downloads

Abstract

In this work, an effective face verification system based on a fusion of the multiscale overlapping blocks binarized statistical image features (BSIF) descriptor and a flip-free distance is proposed. First, we propose a BSIF with overlapping blocks descriptor and extend it to a multiscale framework. Then, after applying dimensionality reduction, the projected vectors for each scale are scored using two prevalent face verification classifiers: triangular similarity metric learning and the Joint Bayesian method. Moreover, a flip-free distance is applied to boost overall performance. Finally, the different scores for different scales are fused using a support vector machine to further improve performance. We evaluate the proposed face verification system under restricted and unrestricted protocols, for which, in both cases, we achieve very competitive results (90.05 and 93.41%) for the problem of face verification on the Labeled Faces in the Wild dataset.

Keywords

Face verification BSIF Joint Bayesian method Triangular similarity metric learning Labeled Faces in the wild Flip-free distance 

Notes

Acknowledgements

This work is supported by National Natural Science Foundation of China (Grant No. 61402307), and National Key Scientific Instrument and Equipment Development Project of China (No.2013YQ49087903).

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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  • Tianyu Geng
    • 1
    • 2
  • Menglong Yang
    • 3
  • Zhisheng You
    • 1
  • Ying Cai
    • 1
  • Feihu Huang
    • 2
  1. 1.College of Computer ScienceSichuan UniversitySichuanChina
  2. 2.National Key Laboratory of Fundamental Science on Synthetic VisionSichuan UniversitySichuanChina
  3. 3.School of Aeronautics and AstronauticsSichuan UniversitySichuanChina

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