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

• المؤلفون الرئيسيون: HUANG, Zhiwu, WANG, R., SHAN, S., CHEN, X.
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2014
• الموضوعات: 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
• الوصول للمادة أونلاين: 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

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...