Title :
Face Recognition Based on Improved Tensor Neighborhood Preserving Embedding
Author_Institution :
Dept. of Comput. Sci. & Technol., Huaqiao Univ., Xiamen, China
Abstract :
Tensor Neighborhood Preserving Embedding(TNPPE) is a efficient subspace dimensionality reduction model for face recognition. However, the singularity problems is still remained. in the paper, we propose an Improved Tensor Neighborhood Preserving Embedding (ITNPE) algorithm for face recognition. We evaluate the algorithm by applying it to YaleB and AR databases. the experiments demonstrate excellent performance of our algorithm for the dimensionality reduction in face recognition.
Keywords :
face recognition; tensors; visual databases; AR database; ITNPE algorithm; YaleB database; face recognition; improved tensor neighborhood preserving embedding; subspace dimensionality reduction model; Algorithm design and analysis; Databases; Face; Face recognition; Image reconstruction; Tensile stress; Vectors; dimensionality reduction; face recognition; tensor image; tensor neighborhood preserving embedding;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
DOI :
10.1109/ISCID.2012.239