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Sketch Synthesized Face Recognition with Deep Learning Models

  • Wei Shao
  • Zhicheng Chen
  • Guangben Lu
  • Xiaokang Tu
  • Yuchun Fang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)

Abstract

Sketch face recognition is of great significance in the field of criminal investigation, Internet search and management. In this paper, we explore the feature presentation of sketch synthesized face images with several deep learning models. In order to complete the matching of heterogeneous images, we propose a modified face synthesis technology that combines sketches and face templates into a human face portrait. Through experiments, we investigate the essential problem of the degree of synthetic with respect to face recognition. Several state-of-the-art Deep Neural Network (DNN) models in face recognition are transferred in feature extraction of sketch synthesized face images. Experiments show that the proposed synthetic method is effective working with the DNN models in sketch face recognition.

Keywords

Heterogeneous face recognition Sketch face recognition CNNs Face synthesis 

Notes

Acknowledgements

The work is funded by the Shanghai Undergraduate Student Innovation Project, the National Natural Science Foundation of China (No. 61170155) and the Shanghai Innovation Action Plan Project (No. 16511101200).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Wei Shao
    • 1
  • Zhicheng Chen
    • 1
  • Guangben Lu
    • 1
  • Xiaokang Tu
    • 1
  • Yuchun Fang
    • 1
  1. 1.School of Computer Engineering and ScienceShanghai UniversityShanghaiChina

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