Multilinear Local Fisher Discriminant Analysis for Face Recognition View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Yucong Peng , Peng Zhou , Hao Zheng , Baochang Zhang , Wankou Yang

ABSTRACT

In this paper, a multilinear local fisher discriminant analysis (MLFDA) framework is introduced for tensor object dimensionality reduction and recognition. MLFDA achieves feature extraction by finding a multilinear projection to map the original tensor space into a tensor subspace that maximize the local between-class scatter as well as minimize the local within-class scatter. The experimental result shows that MLFDA has an outperformance. More... »

PAGES

130-138

Book

TITLE

Biometric Recognition

ISBN

978-3-319-46653-8
978-3-319-46654-5

From Grant

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-46654-5_15

DOI

http://dx.doi.org/10.1007/978-3-319-46654-5_15

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1084843243


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