Fast hierarchical tucker decomposition with single-mode preservation and tensor subspace analysis for feature extraction from augmented multimodal data

2021 ◽  
Vol 445 ◽  
pp. 231-243
Author(s):  
Krzysztof Fonał ◽  
Rafał Zdunek
Keyword(s):  
Feature Extraction ◽  
Single Mode ◽  
Tucker Decomposition ◽  
Subspace Analysis ◽  
Multimodal Data ◽  
Tensor Subspace

Face Recognition and Semantic Features

2011 ◽  
pp. 80-98
Author(s):  
Huiyu Zhou ◽  
Yuan Yuan ◽  
Chunmei Shi
Keyword(s):  
Face Recognition ◽  
Singular Value Decomposition ◽  
Eigenvalue Problem ◽  
Singular Value ◽  
Semantic Features ◽  
Subspace Analysis ◽  
Geometrical Properties ◽  
The Face ◽  
Tensor Subspace ◽  
Value Decomposition

The authors present a face recognition scheme based on semantic features’ extraction from faces and tensor subspace analysis. These semantic features consist of eyes and mouth, plus the region outlined by three weight centres of the edges of these features. The extracted features are compared over images in tensor subspace domain. Singular value decomposition is used to solve the eigenvalue problem and to project the geometrical properties to the face manifold. They compare the performance of the proposed scheme with that of other established techniques, where the results demonstrate the superiority of the proposed method.

Face recognition using second-order discriminant tensor subspace analysis

2011 ◽  
Vol 74 (12-13) ◽  
pp. 2142-2156 ◽  
Author(s):  
Su-Jing Wang ◽  
Chun-Guang Zhou ◽  
Na Zhang ◽  
Xu-Jun Peng ◽  
Yu-Hsin Chen ◽  
...  
Keyword(s):  
Face Recognition ◽  
Second Order ◽  
Subspace Analysis ◽  
Tensor Subspace
Sign in / Sign up

Export Citation Format

Share Document