Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23332
Title: Local face sketch synthesis learning
Authors: Gao, X
Zhong, J
Tao, D
Li, X
Keywords: E-HMM
Facial sketch synthesis
Pseudo-sketch
Selective ensemble
Sketch-photo recognition
Issue Date: 2008
Publisher: Elsevier
Source: Neurocomputing, 2008, v. 71, no. 10-12, p. 1921-1930 How to cite?
Journal: Neurocomputing 
Abstract: Facial sketch synthesis (FSS) is crucial in sketch-based face recognition. This paper proposes an automatic FSS algorithm with local strategy based on embedded hidden Markov model (E-HMM) and selective ensemble (SE). By using E-HMM to model the nonlinear relationship between a photo-sketch patch pair, a series of pseudo-sketch patches, generated based on several learned models for a given photo patch, are integrated with SE strategy to synthesize a finer face pseudo-sketch patch. Finally, the intact pseudo-sketch can be generated by combining all synthesized patches. Experimental results illustrate that the proposed FSS algorithm works well.
URI: http://hdl.handle.net/10397/23332
ISSN: 0925-2312
EISSN: 1872-8286
DOI: 10.1016/j.neucom.2007.10.025
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