Plenary Talks

ICASSP 2014 features a special program of plenary talks on the different aspects of signal processing and their current research challenges. The presentations will be delivered in a plenary session just after lunchtime in the main Cavaniglia Hall.

Tuesday - 6 May

C. Richard Johnson, Jr.
Cornell University, USA
Signal Processing in Computational Art History

Wednesday - 7 May

Chris Bishop
Microsoft Research Cambridge, UK
Model-Based Signal Processing

Thursday - 8 May

Alfonso Farina
Selex ES, Italy
Green radar state of art: theory, practice and way ahead

Friday - 9 May

Jean-Jacques Slotine
Synchronization and detectability in nonlinear networks and biology


Signal Processing in Computational Art History

C. Richard Johnson, Jr. (Cornell University, USA)

A key component of the scholarly analysis of fine art, which recently has expanded significantly under the label of technical art history, utilizes the extraction of features from revealing images of the art object. Within the past seven years painstaking manual methods of feature extraction from images of an art work’s support materials, in particular canvas and paper, have been enhanced with the application of signal processing in projects spearheaded by the speaker. When combined with big data handling capabilities, creating an approach designated here as computational art history, significant advances have been achieved. This talk describes three such emerging applications of digital signal processing to art historical issues of dating and attribution.
• thread counting for weave matching of Old Master paintings on canvas from x-radiographs, which has proven helpful in studies of the paintings of van Gogh, Vermeer, Velazquez, Bouts, and a Poussin
• texture similarity assessment for metadata (manufacturer, surface finish, brand, and date of manufacture) classification of historic photographic papers, in particular silver gelatin and inkjet papers, from raking light photomicrographs
• chain line pattern matching for mold-mate identification of laid papers from low-energy radiographs, initially for the prints of Rembrandt and Durer

C. Richard Johnson, Jr. is the Geoffrey S. M. Hedrick Senior Professor of Engineering and a Stephen H. Weiss Presidential Fellow at Cornell University. He received a PhD in Electrical En- gineering from Stanford University, along with the first PhD minor in Art History granted by Stanford, in 1977. At the start of 2007, after 30 years of research on adaptive feedback systems theory and blind equalization in communication receivers, Professor Johnson accepted a 5-year appointment as an Adjunct Research Fellow of the Van Gogh Museum (Amsterdam, the Netherlands) to facilitate the interaction of art historians and conservation specialists with algorithm-building signal processors. In 2013, Professor Johnson was appointed a Scientific Researcher of the Rijksmuseum (Amsterdam, the Netherlands) and Computational Art History Advisor to the RKD - Netherlands Institute for Art History (the Hague, the Netherlands). Professor Johnson founded the Thread Count Automation Project (TCAP) in collaboration with the Van Gogh Museum in 2007, initiated the Historic Photographic Paper Classification (HPPC) Challenge in cooperation with the Museum of Modern Art in 2010, and launched the Chain Line Pattern (CLiP) Matching Project with the Morgan Library & Museum and the Rijksmuseum in 2012.

Model-Based Signal Processing

Chris Bishop (Microsoft Research Cambridge, UK)

The explosive growth of interest in big data and machine learning over the last few years highlights the need for new tools and techniques to accelerate the development of machine learning and signal processing applications. In this talk I shall give a tutorial introduction to the model-based paradigm in which a solution is expressed through a compact modelling language, and the corresponding custom inference code is then generated automatically. The majority of standard techniques correspond to specific choices for the model and arise naturally as special cases, while variants of these techniques to suit specific applications are easily constructed, and alternative related models can readily be compared. Further advantages compared to traditional hand-coding of solutions include transparency of functionality, and the segregation of modelling code from inference code, while newcomers to the field need only to understand the model specification environment in order to gain access to a huge range of machine learning and signal processing algorithms. The talk will be illustrated with several real-world case studies.

Chris Bishop is a Distinguished Scientist at Microsoft Research Cambridge where he leads the Machine Learning and Perception group. He is also Professor of Computer Science at the University of Edinburgh, and Vice President of the Royal Institution of Great Britain. He has a PhD in quantum field theory, and is a Fellow of the Royal Academy of Engineering, a Fellow of the Royal Society of Edinburgh, and a Fellow of Darwin College Cambridge. Chris is author of the leading textbooks "Neural Networks for Pattern Recognition" (Oxford University Press), and "Pattern Recognition and Machine Learning" (Springer).

Green radar state of art: theory, practice and way ahead

Alfonso Farina (Selex ES, Italy)

Passive radar (passive coherent location, PCL) has been monitored and discussed repeatedly over the last decade by the whole aerospace and electronic systems community, including research institutions, universities, and industry. The tutorial will propose an introduction to the PCL system, showing its intrinsic characteristics and advantages with respect to traditional radars, such as, for instance, eco-compatibility and sustainability.
The state of the art will be presented by the AULOS© passive sensor, which is equipped with Uniform Circular Arrays (UCA). The system is based on Digital Beam Forming (DBF) technique and employs the contemporaneous reception of multiple sources of opportunity. Passive radar systems based on UCA need to identify the FM (Frequency Modulation) and DVB-T (Digital Video Broadcasting - Terrestrial) stations with extremely high accuracy, in terms of geographic position and characteristics of the transmitted signal. As for the geographic position, it is mandatory to determine the azimuth of the station (Direction of Arrival, DOA); to achieve the goal, a very precise goniometry strategy is needed. A priori information on the station position could be not reliable and not accurate enough; thus they need to be confirmed via goniometry. A relevant research item is the “blind” DOA estimation, i.e. DOA estimation not employing a priori information, in an environment heavily affected by multipath. Transmitter DOA is an input to the DBF algorithm.
In this contribution we also present a suitable receiving and processing chain for a DVB-T based Passive Bistatic Radar (PBR) system for both air and maritime surveillance. The presentation is focused on the experimental results achieved in the last year of R&D activities carried out in Selex ES in cooperation with the University of Roma “Sapienza” in the framework of the SeaBilla FP7 project. Specifically results achieved in several test campaigns held in Civitavecchia and Livorno, with both cooperative and opportunity (i.e. Automatic Identification System – AIS equipped vessels) targets will be shown.
The aim of this tutorial is to reflect the current state of the art of passive radar system development in the frame of security and defence, and promising hardware approaches, as well as advanced signal processing and future trends in passive radar.

Alfonso Farina (M’95–SM’98–F’00) received the laurea degree in electronic engineering from the University of Rome, Italy, in 1973. In 1974, he joined Selenia, now Selex ES, where he has been a Manager since May 1988. He was Scientific Director in the Chief Technical Office. He was the Director of the Analysis of Integrated Systems Unit. He was also the Director of Engineering in the Large Systems Business Unit. In 2012, he was the Chief Technology Officer of the Company (SELEX Sistemi Integrati) reporting directly to the President. Today he is Senior Advisor to CTO of Selex ES. In his professional life, he has provided technical contributions to detection, signal, data, image processing, and fusion for the main radar systems conceived, designed, and developed in the company. He has provided leadership in many projects — also conducted in the international arena — in surveillance for ground and naval applications, in airborne early warning and in imaging radar. From 1979 to 1985, he was also Professor of radar techniques at the University of Naples, and in 1985, he was appointed Associate Professor. He is the author of more than 500 peer-reviewed technical publications and the author of books and monographs: Radar Data Processing (Vols. 1 and 2), which were translated in Russian and Chinese (London, UK: Researches Studies Press and New York: Wiley, 1985–1986); Optimized Radar Processors (London, U.K., IEE, Peregrinus. 1987); and Antenna Based Signal Processing Techniques for Radar Systems (Artech House, 1992) . He wrote the chapter “ECCM Techniques” in the Radar Handbook (McGraw-Hill, 2nd ed., 1990, and 3rd ed., 2008), edited by Dr.M. I. Skolnik. Dr. Farina has been session chairman at many international radar conferences. In 1987, he received the Radar Systems Panel Award of IEEE Aerospace and Electronic Systems Society (AESS) for development of radar data processing techniques. He has been the Executive Chair of the International Conference on Information Fusion (Fusion), Florence, Italy, July 10–13, 2006. He has been nominated Fellow of IEEE with the following citation: “For development and application of adaptive signal processing methods for radar systems.” Recently, he has been nominated international fellow of the Royal Academy of Engineering, U.K.; this fellowship was presented to him by HRH Prince Philip, the Duke of Edinburgh. He is the corecipient of the following Best Paper Awards: entitled to B. Carlton of the IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS for 2001 and 2003 and also of the International Conference on Fusion 2005. He has been the leader of the team that won the 2004 First Prize Award for Innovation Technology of Finmeccanica, Italy. This award context has seen the submission of more than 320 projects. This award has been set for the first time in 2004. In September 7, 2006, he received the Annual European Group Technical Achievement Award 2006 by the European Association for Signal, Speech and Image Processing (EURASIP), with the following citation: “For development and application of adaptive signal processing technique in practical radar systems.” He has been the General Chairman of the IEEE Radar Conference, Rome, Italy, May 26–30, 2008. He is a Fellow of the IET (Institution of Engineering and Technology), U.K. He has been recently nominated Fellow of EURASIP, with the following citation: “For contributions to radar system design, signal, data and image processing, data fusion and particularly for the development of innovative algorithms for deployment into practical radar systems.” He is also the recipient of the 2010 IEEE Dennis J. Picard Gold Medal for Radar Technologies and Applications with the following citation: “For continuous, innovative, theoretical and practical contributions to radar systems and adaptive signal processing techniques”. He has been member of the team: “Aulos: the green radar” which was awarded, in May 2013, of the Oscar Masi for the Industrial Innovation, by AIRI (Italian Association for the Industrial Research).

Synchronization and detectability in nonlinear networks and biology

Jean-Jacques Slotine (MIT, USA)

Computation, measurement, and synchronization are key issues in complex networks. Vast nonlinear networks are encountered in biology, for instance, and in neuroscience, where for most tasks the human brain grossly outperforms engineered algorithms using computational elements 7 orders of magnitude slower than their artificial counterparts. We show that nonlinear dynamic systems analysis tools yield simple but highly non-intuitive insights about such issues, and that they also suggest systematic mechanisms to build progressively more refined networks through stable accumulation of functional building blocks and motifs.

Jean-Jacques Slotine was born in Paris in 1959, and received his Ph.D. from the Massachusetts Institute of Technology in 1983. After working at Bell Labs in the computer research department, in 1984 he joined the faculty at MIT, where he is now Professor of Mechanical Engineering and Information Sciences, Professor of Brain and Cognitive Sciences, and Director of the Nonlinear Systems Laboratory. Professor Slotine is the co-author of the textbooks "Robot Analysis and Control" (Wiley, 1986) and "Applied Nonlinear Control" (Prentice-Hall, 1991). He was a member of the French National Science Council from 1997 to 2002, a member of Singapore's A*STAR SigN Advisory Board from 2007 to 2010, and is currently a member of the Scientific Advisory Board of the Italian Institute of Technology. He has held Invited Professor positions at College de France, Ecole polytechnique, Ecole normale superieure, Universita di Roma La Sapienza, and ETH Zurich.