Title :
Local Regression Model for Automatic Face Sketch Generation
Author :
Ji, Naye ; Chai, Xiujuan ; Shan, Shiguang ; Chen, Xilin
Author_Institution :
Key Lab. of Intell. Inf. Process., Chinese Acad. of Sci., Beijing, China
Abstract :
As one of the important artistic styles of portrait, sketch portrait has wide applications for both digital entertainment and law enforcement. In this paper, an automatic face sketch generation approach is presented by learning from photo-sketch pair examples. Specifically, the relationship between a face photo and its corresponding face sketch is learned on image patch level. By applying this relationship to the input face photo patch, we can infer the output face sketch patch by exploiting some regression techniques such as kNN, the Lasso and so on. Via our local regression model, we can synthesize an appealing sketch portrait from a given face photo in a few minutes. Experiments conducted on CUHK database have shown that our results are more compelling than previous methods especially in two respects: (1) our synthesized sketches preserve more identity information of the original face photo, (2) our synthesized sketches presents more pencil sketch texture.
Keywords :
image processing; learning (artificial intelligence); regression analysis; automatic face sketch generation; face photo patch; face sketch patch; image patch level; learning-based strategy; local regression model; pencil sketch texture; photo-sketch; sketch portrait; Databases; Face; Hair; Law enforcement; Measurement; Rendering (computer graphics); Training; face sketch generation; k nearest neigbor; lasso; local regression;
Conference_Titel :
Image and Graphics (ICIG), 2011 Sixth International Conference on
Conference_Location :
Hefei, Anhui
Print_ISBN :
978-1-4577-1560-0
Electronic_ISBN :
978-0-7695-4541-7
DOI :
10.1109/ICIG.2011.84