Component SPD matrices: A low-dimensional discriminative data descriptor for image set classification

Component SPD matrices: A low-dimensional discriminative data descriptor for image set classification

Abstract In pattern recognition, the task of image set classification has often been performed by representing data using symmetric positive definite (SPD) matrices, in conjunction with the metric of the resulting Riemannian manifold. In this paper, we propose a new data representation framework for...

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Bibliographic Details
Main Authors: Kai-Xuan Chen, Xiao-Jun Wu
Format: Article
Language:English
Published: SpringerOpen 2018-08-01
Series:Computational Visual Media
Subjects:
symmetric positive definite (SPD) matrices
Riemannian kernel
image classification
Riemannian manifold
Online Access:http://link.springer.com/article/10.1007/s41095-018-0119-7

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http://link.springer.com/article/10.1007/s41095-018-0119-7

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