Mixed Region Covariance Discriminative Learning for Image Classification on Riemannian Manifolds
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Covariance matrices, known as symmetric positive definite (SPD) matrices, are usually regarded as points lying on Riemannian manifolds.
We describe a new covariance descriptor, which could improve the discriminative learning ability of region covariance descriptor by taking into account the mean of feature vectors.
Due to the specific geometry of Riemannian manifolds, classical learning methods cannot be directly used on it.
In this paper, we propose a subspace projection framework for the classification task on Riemannian manifolds and give the mathematical derivation for it.
It is different from the common technique used for Riemannian manifolds, which is to explicitly project the points from a Riemannian manifold onto Euclidean space based upon a linear hypothesis.
Under the proposed framework, we define a Gaussian Radial Basis Function- (RBF-) based kernel with a Log-Euclidean Riemannian Metric (LERM) to embed a Riemannian manifold into a high-dimensional Reproducing Kernel Hilbert Space (RKHS) and then project it onto a subspace of the RKHS.
Finally, a variant of Linear Discriminative Analyze (LDA) is recast onto the subspace.
Experiments demonstrate the considerable effectiveness of the mixed region covariance descriptor and the proposed method.
American Psychological Association (APA)
Liu, Xi& Ma, Zhengming& Niu, Guo. 2019. Mixed Region Covariance Discriminative Learning for Image Classification on Riemannian Manifolds. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1194257
Modern Language Association (MLA)
Liu, Xi…[et al.]. Mixed Region Covariance Discriminative Learning for Image Classification on Riemannian Manifolds. Mathematical Problems in Engineering No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1194257
American Medical Association (AMA)
Liu, Xi& Ma, Zhengming& Niu, Guo. Mixed Region Covariance Discriminative Learning for Image Classification on Riemannian Manifolds. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1194257
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194257