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Linear local tangent space alignment and application to face recognition
- Source :
-
Neurocomputing . Mar2007, Vol. 70 Issue 7-9, p1547-1553. 7p. - Publication Year :
- 2007
-
Abstract
- In this paper, linear local tangent space alignment (LLTSA), as a novel linear dimensionality reduction algorithm, is proposed. It uses the tangent space in the neighborhood of a data point to represent the local geometry, and then aligns those local tangent spaces in the low-dimensional space which is linearly mapped from the raw high-dimensional space. Since images of faces often belong to a manifold of intrinsically low dimension, we develop LLTSA algorithm for effective face manifold learning and recognition. Comprehensive comparisons and extensive experiments show that LLTSA achieves much higher recognition rates than a few competing methods. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 70
- Issue :
- 7-9
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 24301004
- Full Text :
- https://doi.org/10.1016/j.neucom.2006.11.007