Facial sketch synthesis using direct combined model
Ching‐Ting Tu, Jenn-Jier James Lien · 2010
Automatically synthesizing the facial sketches of a facial image is highly challenging since facial images typically exhibit a wide range of poses, expressions and scales, and have differing degrees of illumination and/or occlusion. When the facial sketches are to be synthesized in the unique sketching style of a particular artist, the problem becomes even more complex. This study develops an automatic facial sketch synthesis system based on a novel direct combined model (DCM) algorithm carrying three major advantages: First, DCM approach takes account of both the local details of each facial feature and the global geometric structure of the face, and thus the synthesized sketches more accurately mimic the caricatures drawn by the artist. Second, although the training database contains only full-frontal facial images with a neutral expression, sketches with a wide variety of facial poses, gaze directions and facial expressions can be successfully synthesized. Third, previous synthesizing proposals are heavily reliant on the quality of the texture reconstruction results, which in turn are highly sensitive to occlusion and lighting effects in the input image. DCM approach accurately produces lifelike synthesized facial sketches without the need to restore the texture information lost as a result of such unfavorable conditions.