Graph-based methods have attracted interest in areas such as computer vision, signal processing and network science. In this talk, we will present some advances from our research on graph-theoretic approaches for clustering and segmentation. We will focus on two approaches: 1) An unsupervised approach where we extend the active contours of computer vision to arbitrary graphs by developing efficient finite difference schemes and geometric approximations of gradient and curvature, for which we provide theoretical results on their convergence in probability and asymptotic error bounds for the class of random geometric graphs. 2) A supervised approach where we develop graph-driven diffusion processes on arbitrary graphs by relating the SIR epidemic propagation model to the random walker algorithm. This helps us to develop the normalized random walker by integrating the importance of each node to the final clustering or segmentation solution. For both approaches, we provide experimental results for graph clustering and image segmentation.
Petros Maragos received the Diploma in E.E. from the National Technical University of Athens (NTUA) in 1980 and the M.Sc. and Ph.D. degrees from Georgia Tech, Atlanta, in 1982 and 1985. In 1985, he joined the faculty of the Division of Applied Sciences at Harvard University, where he worked for eight years as professor of electrical engineering affiliated with the Harvard Robotics Lab. In 1993, he joined the faculty of the School of ECE at Georgia Tech. During periods of 1996-98 he had a joint appointment as director of research at the Institute of Language and Speech Processing in Athens. Since 1998, he has been working as a professor at the NTUA School of ECE. He has been a visiting scientist at MIT in 2012 and visiting professor at UPenn in 2016. He is currently the Director of the NTUA Division of Signals, Control and Robotics. His research and teaching interests include signal processing, systems theory, machine learning, image processing and computer vision, audio and speech processing, and robotics. In the above areas he has published numerous papers, book chapters, and has also co-edited three Springer research books, one on multimodal processing and interaction and two on shape analysis. He has served as: Associate Editor for the IEEE Trans. on ASSP, IEEE Trans. on PAMI, and editorial board member and guest editor for several journals on signal processing, image analysis and vision; co-organizer of several conferences and workshops on image processing, computer vision, multimedia and robotics; member of IEEE SPS committees. He has currently co-organized EUSIPCO 2017 as general co-chair. He has also served as member of the Greek National Council for Research and Technology.
His is the recipient or co-recipient of several awards for his academic work, including a 1987-1992 National Science Foundation Presidential Young Investigator Award, a 1988 IEEE SPS Young Author Best Paper Award, a 1994 IEEE SPS Senior Best Paper Award, the 1995 IEEE W.R.G. Baker Prize Award for the most outstanding original paper,the 1996 Pattern Recognition Society's Honorable Mention Award, the EURASIP 2007 Technical Achievement Award for contributions to nonlinear signal, image and speech processing, and the Best Paper Award of the IEEE CVPR-2011 Gesture Recognition Workshop. He was elected a Fellow of IEEE in 1995 and a Fellow of EURASIP in 2010 for his research contributions. He has been elected IEEE SPS Distinguished Lecturer for 2017-2018.
