Object tracking in video-surveillance

This paper faces the automatic object tracking problem in a video-surveillance task. A previously selected and then identified target has to be retrieved in the scene under investigation because it is lost due to masking, occlusions, or quick and unexpected movements. A two-step procedure is used, firstly motion detection is used to determine a candidate target in the scene, secondly using a semantic categorization and Content Based Image Retrieval techniques, the candidate target is identified whether it is the one that was lost or not. The use of Content Based Image Retrieval serves as support to the search problem and is performed using a reference data base which was populated a priori. The article is published in the original. Davide Moroni (Magenta, 1977), M.Sc. in Mathematics honours degree from the University of Pisa in 2001, dipl. at the Scuola Normale Superiore of Pisa in 2002, Ph.D. in Mathematics at the University of Rome ‘La Sapienza’ in 2006, is a research fellow at the Institute of Information Science and Technologies of the Italian National Research Council, in Pisa. His main interests include geometric modelling, computational topology, image processing and medical imaging. At present he is involved in a number of European research projects working in discrete geometry and scene analysis. Gabriele Pieri (Pescia, 1974), M.Sc. (2000) in Computer Science from the University of Pisa, since 2001 joined the “Signals and Images” Laboratory at ISTI-CNR, Pisa, working in the field of image analysis. His main interests include neural networks, machine learning, industrial diagnostics and medical imaging. He is author of more than twenty papers.