Linear local tangent space alignment and application to face recognition

Tianhao Zhang, Jie Yang, Deli Zhao, Xinliang Ge
2007 Neurocomputing  
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
more » ... g and recognition. Comprehensive comparisons and extensive experiments show that LLTSA achieves much higher recognition rates than a few competing methods. r
doi:10.1016/j.neucom.2006.11.007 fatcat:h7grcuz6nfds5hgawui7zchc2u