Cascaded Face Sketch Synthesis under Various Illuminations.

Abstract

Face sketch synthesis from a photo is of significant importance in digital entertainment. An intelligent face sketch synthesis system requires a strong robustness to lighting variations. Under uncontrolled lighting conditions in real-world settings, such a system will perform consistently well and have little restriction on the lighting conditions. However, previous face sketch synthesis methods tend to synthesize sketches under well-controlled lighting conditions. These methods are sensitive to lighting variations and produce unsatisfactory results when the lighting condition varies. In this paper, we propose a novel cascaded face sketch synthesis framework composed of a multiple feature generator and a cascaded low-rank representation. The multiple feature generator not only produces a generated sketch feature consistent with an artist's drawing style but also extracts a photo feature that is robust to various illuminations. Both features ensure that given a photo patch, the optimal sketch candidates can be selected from the database. The cascaded low-rank representation enables a gradual reduction in the gap between the synthesized face sketch and the corresponding artistdrawn sketch. Experimental results illustrate that the proposed cascaded framework generates realistic sketches on par with the current methods on the Chinese University of Hong Kong face sketch database under well-controlled illuminations. Moreover, this framework exhibits greatly improved performance compared to these methods on the extended Chinese University of Hong Kong face sketch database and Chinese celebrity face photos from the web under different illuminations. We argue that this framework paves a novel way for the implementation of computer-aided optical systems that are of essential importance in both face sketch synthesis and optical imaging.