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Many signal and image processing applications, including texture analysis, radar detection or EEG signal classification, require the computation of a centroid from a set of covariance matrices. The most popular approach consists in considering the center of mass. While efficient, this estimator is not robust to outliers arising from the inherent variability of the data or from faulty measurements. To overcome this, some authors have proposed to use the median as a more robust estimator. Here,doi:10.1109/eusipco.2016.7760638 dblp:conf/eusipco/IleaHSBGB16 fatcat:rcv2oadyxjepffhqmzkja72liy