Robust Low-Rank Subspace Segmentation with Semidefinite Guarantees
Robust Low-Rank Subspace Segmentation with Semidefinite Guarantees
Recently there is a line of research work proposing to employ Spectral Clustering (SC) to segment (group) high-dimensional structural data such as those (approximately) lying on subspaces or low-dimensional manifolds. By learning the affinity matrix in the form of sparse reconstruction, techniques proposed in this vein often considerably boost the …