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Hierarchical multi-label framework for robust face recognition | IEEE Conference Publication | IEEE Xplore

Hierarchical multi-label framework for robust face recognition


Abstract:

In this paper, we propose a patch based face recognition framework. First, a face image is iteratively divided into multi-level patches and assigned hierarchical labels. ...Show More

Abstract:

In this paper, we propose a patch based face recognition framework. First, a face image is iteratively divided into multi-level patches and assigned hierarchical labels. Second, local classifiers are built to learn the local prediction of each patch. Third, the hierarchical relationships defined between local patches are used to obtain the global prediction of each patch. We develop three ways to learn the global prediction: majority voting, ℓ1-regularized weighting, and decision rule. Last, the global predictions of different levels are combined as the final prediction. Experimental results on different face recognition tasks demonstrate the effectiveness of our method.
Date of Conference: 19-22 May 2015
Date Added to IEEE Xplore: 02 July 2015
Electronic ISBN:978-1-4799-7824-3
Print ISSN: 2376-4201
Conference Location: Phuket, Thailand

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