Date & Time:
Thursday, March 21, 2013; 12:00 PM
Graphs have long been used in a wide variety of problems, such analysis of social networks, machine learning, network protocol optimization, decoding of LDPCs or image processing. Techniques based on spectral graph theory provide a "frequency" interpretation of graph data and have proven to be quite popular in multiple applications.
In the last few years, a growing amount of work has started extending and complementing spectral graph techniques, leading to the emergence of "Graph Signal Processing" as a broad research field. A common characteristic of this recent work is that it considers the data attached to the vertices as a "graph-signal" and seeks to create new techniques (filtering, sampling, interpolation), similar to those commonly used in conventional signal processing (for audio, images or video), so that they can be applied to these graph signals.
In this talk, we first introduce some of the basic tools needed in developing new graph signal processing operations. We then introduce our design of wavelet filterbanks of graphs, which for the first time provides a multi-resolution, critically-sampled, frequency- and graph-localized transforms for graph signals. We conclude by providing several examples of how these new transforms and tools can be applied to existing problems. Time permitting, we will discuss applications to image processing, depth video compression, recommendation system design and network optimization.
Prof. Antonio Ortega
University of Southern California
Antonio Ortega received the Telecommunications Engineering degree from the Universidad Politecnica de Madrid, Madrid, Spain in 1989 and the Ph.D. in Electrical Engineering from Columbia University, New York, NY in 1994. At Columbia he was supported by a Fulbright scholarship. In 1994 he joined the Electrical Engineering department at the University of Southern California (USC), where he is currently a Professor, previously served as Associate Chair of EE-Systems. He has served as director of the Signal and Image Processing Institute at USC. He is a Fellow of the IEEE, and a member of ACM and APSIPA. He has been a member of the Board of Governors of the IEEE Signal Processing Society, and technical program co-chair of ICIP 2008, MMSP 1998 and ICME 2002. He is general chair of the GlobalSIP Symposium on Graph Signal Processing and technical program co-chair of PCS 2013. He has served as Associate Editor of the IEEE Transactions on Image Processing, Signal Processing Letters and Area Editor (Feature Articles) of the IEEE Signal Processing Magazine. He is the inaugural Editor-in-Chief of the APSIPA Transactions on Signal and Information Processing. He received the NSF CAREER award, the 1997 IEEE Communications Society Leonard G. Abraham Prize Paper Award, the IEEE Signal Processing Society 1999 Magazine Award, 2006 EURASIP Journal of Advances in Signal Processing Best Paper Award, the ICIP 2011 best paper award and best paper at Globecom 2012. His research interests are in the areas of multimedia compression, communications and signal analysis. He has supervised over 30 PhD theses at USC and has co-authored over 300 papers in international conferences and journals.