Lighting and Pose Robust Face Sketch Synthesis
Refereed conference paper presented and published in conference proceedings


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摘要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.
著者Zhang W, Wang XG, Tang XO
會議名稱11th European Conference on Computer Vision
會議開始日05.09.2010
會議完結日11.09.2010
會議地點Heraklion
會議國家/地區希臘
期刊名稱Lecture Notes in Artificial Intelligence
詳細描述organized by Daniilidis, Kostas; Maragos, Petros; Paragios, Nikos,
出版年份2010
月份1
日期1
卷號6316
出版社SPRINGER-VERLAG BERLIN
頁次420 - 433
國際標準書號978-3-642-15566-6
國際標準期刊號0302-9743
語言英式英語
Web of Science 學科類別Computer Science; Computer Science, Artificial Intelligence; Computer Science, Theory & Methods; Imaging Science & Photographic Technology

上次更新時間 2021-17-09 於 01:13