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.
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© 2011 Springer-Verlag Berlin Heidelberg
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Chang, L., Zhou, M., Deng, X., Wu, Z., Han, Y. (2011). Face Sketch Synthesis via Multivariate Output Regression. In: Jacko, J.A. (eds) Human-Computer Interaction. Design and Development Approaches. HCI 2011. Lecture Notes in Computer Science, vol 6761. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21602-2_60
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DOI: https://doi.org/10.1007/978-3-642-21602-2_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21601-5
Online ISBN: 978-3-642-21602-2
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