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Over the past few decades, significant progress has been made in clustering high-dimensional data sets distributed around a collection of linear and affine subspaces. This article presented a review of such progress, which included a number of existing subspace clustering algorithms together with an experimental evaluation on the motion segmentation and face clustering problems in computer vision.
Renè Vidal (Fri,) studied this question.