1. A method for video anomaly detection based upon a sparsity model, said method comprising: computing at least two descriptors of an event from video; combining said at least two descriptors to form an event matrix with respect to said event; performing a sparse reconstruction of said event matrix with respect to an over complete dictionary of training events represented by said at least two descriptors; and determining if said event is anomalous based on an analysis of said sparse reconstruction.