Face Sketch Synthesis System Utilizing Both Global Structure and Local Detailed Texture Components

• Main Authors: Yu-Hsien Chan, 詹于賢
• Other Authors: 凃瀞珽
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/9ju8k3

碩士 === 淡江大學 === 資訊工程學系碩士班 === 103 === This study developed a facial sketch synthesis system based on the two-dimensional direct combined model (2DDCM) and the Markov Random Field (MRF) approaches that employs a large collection of photo/sketch pairwise training samples. The proposed synthesis framework achieves facial sketch generation by addressing the following key issues. First, we directly combine each photo and sketch pairwise sample in a concatenated form in order to completely preserve their relationship. Second, photo and sketch images are formed as two–dimensional matrices instead of vectors in order to preserve the facial geometry. Third, both the vertical and the horizontal facial-geometry features are considered in 2DDCM approach. Finally, the proposed framework integrates both the parametric-based 2DDCM approach with the non-parametric-based Markov Random Field (MRF) approach, where the function of former one is to generate facial sketches with correct facial geometry, and the function of later one is used to generate facial sketches with more detailed textures. Accordingly, as the human drawing process, both the global facial geometry and the local detailed textures are included in the synthesis results. Experiments demonstrate our approach can synthesize high quality reconstructed facial sketches from given unseen photos.