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Local face sketch synthesis learning

Gao, X. and Zhong, J. and Tao, D. and Li, Xuelong (2008) Local face sketch synthesis learning. Neurocomputing 71 (10-12), pp. 1921-1930. ISSN 0925-2312.

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.neucom.2007.10.025

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.

Item Type: Article
Keyword(s) / Subject(s): Facial sketch synthesis, sketch–photo recognition, E-HMM, selective ensemble, pseudo-sketch
School or Research Centre: Birkbeck Schools and Research Centres > School of Business, Economics & Informatics > Computer Science and Information Systems
Depositing User: Administrator
Date Deposited: 04 Feb 2011 15:57
Last Modified: 17 Apr 2013 12:18
URI: http://eprints.bbk.ac.uk/id/eprint/1863

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