Computer Vision – ECCV 2010

Volume 6316 of the series Lecture Notes in Computer Science pp 420-433

Lighting and Pose Robust Face Sketch Synthesis

  • Wei ZhangAffiliated withDepartment of Information Engineering, The Chinese University of Hong Kong
  • , Xiaogang WangAffiliated withDepartment of Electronic Engineering, The Chinese University of Hong Kong
  • , Xiaoou TangAffiliated withDepartment of Information Engineering, The Chinese University of Hong KongShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

* Final gross prices may vary according to local VAT.

Get Access


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.