Lighting and Pose Robust Face Sketch Synthesis

  • Wei Zhang
  • Xiaogang Wang
  • Xiaoou Tang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6316)

Abstract

Automatic face sketch synthesis has important applications in law enforcement and digital entertainment. Although great progress has been made in recent years, previous methods only work under well controlled conditions and often fail when there are variations of lighting and pose. In this paper, we propose a robust algorithm for synthesizing a face sketch from a face photo taken under a different lighting condition and in a different pose than the training set. It synthesizes local sketch patches using a multiscale Markov Random Field (MRF) model. The robustness to lighting and pose variations is achieved in three steps. Firstly, shape priors specific to facial components are introduced to reduce artifacts and distortions caused by variations of lighting and pose. Secondly, new patch descriptors and metrics which are more robust to lighting variations are used to find candidates of sketch patches given a photo patch. Lastly, a smoothing term measuring both intensity compatibility and gradient compatibility is used to match neighboring sketch patches on the MRF network more effectively. The proposed approach significantly improves the performance of the state-of-the-art method. Its effectiveness is shown through experiments on the CUHK face sketch database and celebrity photos collected from the web.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Wei Zhang
    • 1
  • Xiaogang Wang
    • 2
  • Xiaoou Tang
    • 1
    • 3
  1. 1.Department of Information EngineeringThe Chinese University of Hong Kong 
  2. 2.Department of Electronic EngineeringThe Chinese University of Hong Kong 
  3. 3.Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesChina

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