Learning Euclidean-to-Riemannian metric for point-to-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: Euclidean-to-Riemannian metric learning; point-to-set classification; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6396; https://ink.library.smu.edu.sg/context/sis_research/article/7399/viewcontent/Learning_Euclidean_to_Riemannian_Metric_for_Point_to_Set_Classification.pdf
• Institution: Singapore Management University

In this paper, we focus on the problem of point-to-set classification, where single points are matched against sets of correlated points. Since the points commonly lie in Euclidean space while the sets are typically modeled as elements on Riemannian manifold, they can be treated as Euclidean points...