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This paper presents a novel method for cortical surface atlasing. Group-wise registration is performed through a discrete optimisation framework that seeks to simultaneously improve pairwise correspondences between surface feature sets, whilst minimising a global cost relating to the rank of the feature matrix. It is assumed that when fully aligned, features will be highly linearly correlated, and thus have low rank. The framework is regularised through use of multi-resolution control pointdoi:10.1109/cvprw.2016.62 dblp:conf/cvpr/RobinsonGRR16 fatcat:fjwkarb3crcw5j2tuywlsql5o4