A Riemannian network for SPD matrix learning

• Main Authors: HUANG, Zhiwu, VAN, Gool L.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Artificial intelligence; Eigenvalues and eigenfunctions; Geometry; Mathematical transformations; Network architecture; Stochastic systems; Video signal processing; Artificial Intelligence and Robotics; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/6542; https://ink.library.smu.edu.sg/context/sis_research/article/7545/viewcontent/A_riemannian_network_for_SPD_matrix_learning.pdf

Symmetric Positive Definite (SPD) matrix learning methods have become popular in many image and video processing tasks, thanks to their ability to learn appropriate statistical representations while respecting Riemannian geometry of underlying SPD manifolds. In this paper we build a Riemannian netwo...