Face sketch synthesis via multivariate output regression

Authors:
Liang Chang;Mingquan Zhou;Xiaoming Deng;Zhongke Wu;Yanjun Han
Affiliations:
College of Information Science and Technology, Beijing Normal University, Beijing, P.R. China;College of Information Science and Technology, Beijing Normal University, Beijing, P.R. China;Institute of Software, Chinese Academy of Sciences, Beijing, P.R. China;College of Information Science and Technology, Beijing Normal University, Beijing, P.R. China;Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China
Venue:
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: design and development approaches - Volume Part I
Year:
2011

Citing 5
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Abstract

This paper presents a multivariate output regression based method to synthesize face sketches from photos. The training photos and sketches are divided into small image patches. For each pairs of photo patch and its corresponding sketch patch in training data, a local regression model is built by multivariate output regression methods such as kernel ridge regression and relevance vector machine (RVM). Compared with commonly used single-output regression, multivariate output regression can enforce the synthesized sketch patches with structure constraints. Experiments are given to show the validity and effectiveness of the approach.