Hybrid euclidean-and-riemannian metric learning for image set classification

• Main Authors: HUANG, Zhiwu, WANG, R., SHAN, S., CHEN, X.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Gaussian Mixture Model; Reproduce Kernel Hilbert Space; Symmetric Positive Definite Matrice; Symmetric Positive Definite; Heterogeneous Space; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6395; https://ink.library.smu.edu.sg/context/sis_research/article/7398/viewcontent/Hybrid_Euclidean_and_Riemannian_Metric.pdf
• Institution: Singapore Management University

We propose a novel hybrid metric learning approach to combine multiple heterogenous statistics for robust image set classification. Specifically, we represent each set with multiple statistics – mean, covariance matrix and Gaussian distribution, which generally complement each other for set modeling...