BBAuthors: Ackermann, H.; Advisor: -; Participants: - (2017)
Sparse subspace clustering (SSC) is an elegant approach for unsupervisedsegmentationifthedatapointsofeachclusterare located in linear subspaces. This model applies, for instance, in motion segmentation if some restrictions on the camera model hold. SSC requires that problems based on the l1-norm are solved to infer which points belong to the same subspace. If these unknown subspaces are well-separated this algorithm is guaranteed to succeed. The algorithm rests upon the assumption that points on the same subspace are well spread. The question what happens if this condition is violated has not yet been investigated. In this work, the effect of particular distributions on the same subsp... 
