k-means on Positive Definite Matrices, and an Application to Clustering in Radar Image Sequences

2020-08-08Code Available0· sign in to hype

Daniel Fryer, Hien Nguyen, Pascal Castellazzi

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Code

github.com/frycast/kmspd
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Abstract

We state theoretical properties for k-means clustering of Symmetric Positive Definite (SPD) matrices, in a non-Euclidean space, that provides a natural and favourable representation of these data. We then provide a novel application for this method, to time-series clustering of pixels in a sequence of Synthetic Aperture Radar images, via their finite-lag autocovariance matrices.

Tasks

Clustering Time Series Time Series Analysis Time Series Clustering

k-means on Positive Definite Matrices, and an Application to Clustering in Radar Image Sequences

Code

Abstract

Tasks

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