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Andrea Cavallaro

Professor of Multimedia Signal Processing and Director of the Centre for Intelligent Sensing at Queen Mary University of London, UK
Andrea Cavallaro is Professor of Multimedia Signal Processing and Director of the Centre for Intelligent Sensing at Queen Mary University of London, UK. He received his Ph.D. in Electrical Engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 2002. He was a Research Fellow with British Telecommunications (BT) in 2004/2005 and was awarded the Royal Academy of Engineering teaching Prize in 2007; three student paper awards on target tracking and perceptually sensitive coding at IEEE ICASSP in 2005, 2007 and 2009; and the best paper award at IEEE AVSS 2009. Prof. Cavallaro is Associate Editor for the IEEE Transactions on Image Processing. He is an elected member of the IEEE Signal Processing Society, Image, Video, and Multidimensional Signal Processing Technical Committee, and chair of its Awards committee. He served as an elected member of the IEEE Signal Processing Society, Multimedia Signal Processing Technical Committee, as Associate Editor for the IEEE Transactions on Multimedia and the IEEE Transactions on Signal Processing, as Area Editor for the IEEE Signal Processing Magazine and as Guest Editor for eleven international journals. He was General Chair for IEEE/ACM ICDSC 2009, BMVC 2009, M2SFA2 2008, SSPE 2007, and IEEE AVSS 2007. Prof. Cavallaro was Technical Program chair of IEEE AVSS 2011, the European Signal Processing Conference (EUSIPCO 2008) and of WIAMIS 2010. He has published more than 130 journal and conference papers, one monograph on Video tracking (2011,Wiley) and three edited books: Multi-camera networks (2009, Elsevier); Analysis, retrieval and delivery of multimedia content (2012, Springer); and Intelligent multimedia surveillance (2013, Springer).
Talk Title:
Smart Video Data
Talk Abstract:
Video capturing devices are ubiquitous. Cameras with microphones are increasingly worn by people, mounted on dashboards and micro-drones; installed in hallways, streets and stores. In this talk I will cover techniques that automatically extract actionable information from videos and camera networks to learn patterns of behaviour, to detect anomalies and to help predict intentions. I will focus on recent applications that are offering extraordinary opportunities to improve our businesses, safety and quality of life; discuss the associated scientific challenges and privacy implications.
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