A black hole novelty detector for video analysis

A black hole is a region of space that has so much mass concentrated in it that there is no way training data for a nearby object to escape its gravitational pull. In this paper we are inspired by this phenomenon to create a new form of novelty detector. We consider the of a given class as a black hole. For multiclass data we are dealing with multiple black holes. A test point is pulled by the centroids of different black holes as well as its K nearest neighbours. The gravitational pull is modelled as an iterative process, where the forces acting on a point are constantly changing with time as the test point moves in multi-dimensional space corresponding to. these forces. Once the algorithm has converged, a thresholding scheme is applied to determine whether the test point has been pulled within the boundary of the black hole or not. Any points that lie outside all known black holes are deemed to be novel. We compare this novelty detector with other well-known models of novelty detection on a video analysis application and show very promising results.