Patch-Based Principal Covariance Discriminative Learning for Image Set Classification

Patch-Based Principal Covariance Discriminative Learning for Image Set Classification

Image set classification has attracted increasing attention with respect to the use of significant amounts of within-set information. The covariance matrix is a natural and effective descriptor for describing image sets. Non-singular covariance matrices, known as symmetric positive definite (SPD) ma...

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Bibliographic Details
Main Authors: Hengliang Tan, Ying Gao
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Covariance matrix
Riemannian manifolds
image set classification
maximal linear patch
linear discriminant analysis
principal component analysis
Online Access:https://ieeexplore.ieee.org/document/7997713/

Internet

https://ieeexplore.ieee.org/document/7997713/

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