Electronic Letters on Computer Vision and Image Analysis 13(2):15-16, 2014 Detecting and indexing moving objects for Behavior Analysis by Video and Audio Interpretation

In the last decades we have assisted to a growing need for security in many public environments. This con-sideration has lead the proliferation of cameras and microphones, which represent a suitable solution for their relative low cost of maintenance, the possibility of installing them virtually everywhere and, finally, the capa-bility of analyzing more complex events. However, the main limitation of traditional audio-video surveillance systems lies in the so called psychological overcharge issue of the human operators responsible for security, that causes a decrease in their capabilities to analyze raw data flows from multiple sources of multimedia infor-mation. For the above mentioned reasons, it would be really useful to design an intelligent surveillance system, able to provide images and video with a semantic interpretation, for trying to bridge the gap between their low-level representation in terms of pixels, and the high-level, natural language description that a human would give about them. The aim of this thesis [11] is to face the above mentioned issues, as fascinating as challenging. The proposed system analyzes videos and by extracting trajectories of objects populating the scene (tracking): trajectory is a very discriminant feature, since the movement of objects in a scene is not random, but instead have an underlying structure which can be exploited to build some models. The main novelties of the proposed tracking algorithm lie in the following aspects: first, the entire history of each object populating the scene i