Clustering Positive Definite Matrices by Learning Information Divergences
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Stanitsas, Panagiotis; Cherian, Anoop; Morellas, Vassilios; Papanikolopoulos, Nikolaos
Description
Data representations based on Symmetric Positive Definite (SPD) matrices are gaining popularity in visual learning applications. When comparing SPD matrices, measures based on non-linear geometries often yield beneficial results. However, a manual selection process is commonly used to identify the appropriate measure for a visual learning application. In this paper, we study the problem of clustering SPD matrices while automatically learning a suitable measure. We propose a novel formulation...[Show more]
Collections | ANU Research Publications |
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Date published: | 2017 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/313210 |
Source: | Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017 |
DOI: | 10.1109/ICCVW.2017.155 |
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