Adaptive multi-granularity sparse subspace clustering.

•The notion of scored kNN (SkNN) is proposed to guide the propagation of neighborhoods from fine granularity to coarse.•The existence of a solution to multi-granularity sparse subspace representation is proved.•The consistency of sparse subspace representation at all multi-granularity levels is captured effectively by the proposed AMGSSC.•The smoothness of learned sparse representation by using AMGLSSC increases the intra-class connectivity of adjacency graph.