Local face sketch synthesis learning

Authors:
Xinbo Gao;Juanjuan Zhong;Dacheng Tao;Xuelong Li
Affiliations:
School of Electronic Engineering, Xidian University, Xi'an, Shaanxi, PR China;School of Electronic Engineering, Xidian University, Xi'an, Shaanxi, PR China;Biometrics Research Centre, The Hong Kong Polytechnic University, Hong Kong, PR China;School of Computer Science and Information Systems, Birkbeck College, University of London, UK
Venue:
Neurocomputing
Year:
2008

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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.