Final program download here

Keynote talks

Title: Compressed sensing and sparsity for intelligent information processing

Abstract: This talk addresses the use of compressed sensing and its underlying sparsity model to tackle modern data handling problems. Compressed sensing is an innovative signal sensing and representation paradigm that is significantly more efficient than conventional sampling as described by Shannon’s theorem. This very compact representation has many potential advantages in the areas of signal acquisition and communication, as well as visual information processing. The talk first covers compressed sensing fundamentals, reviewing the basic theory and results. Then it explores various application scenarios where compressed sensing and sparsity yield a significant performance enhancement over the state of the art. Such applications include communication in distributed systems, big data, camera identification for image forensics applications, hyperspectral imaging, encryption, and so forth. In all these applications, compressed sensing allows to employ a compact representation reducing memory, storage, computation and energy requirements, enabling novel applications and opening new scenarios.

Speaker bio:

Enrico Magli is currently an Associate Professor at the Politecnico di Torino, and is the director of the Image Processing Lab. His research interests are in the field of multimedia signal processing and networking, compressed sensing, image/video analysis, compression, communication and security.

He is an associate editor of the IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Multimedia, and EURASIP Journal on Image and Video Processing. He is general co-chair of IEEE ICME 2015 and has been general chair of MMSP 2013, TPC co-chair of ICME 2012, VCIP 2012, VCIP 2014, MMSP 2011 and IMAP 2007.

He has published 54 papers in refereed international journals. Moreover, he has contributed 4 book chapters, and has coauthored over 130 conference papers. He is a co-recipient of the IEEE Geoscience and Remote Sensing Society 2011 Transactions Prize Paper Award and has received the 2011 and 2014 Best Associate Editor Award of IEEE Transactions on Circuits and Systems for Video Technology. He has been awarded an ERC starting grant and an ERC proof of concept grant in the area of compressed sensing.

Title: UWB Radar Signal Processing for Human Beings Detection, Localization and Tracking

At the beginning of the 21th century, the human society is facing quit a number of specific social trends. The increasing density of population of towns and town agglomerations, criminality growing and political tensions producing terrorism can be ranked among them.

A high density of the population at disasters (e.g. earthquakes, tsunamis, earth slides, avalanches, building collapses) results in a high number of injured persons. At these events, a lot of persons can survive the most critical moments of the emergency events. However, the survivors have often limited capability of the motion (e.g. they are under rubble or snow) or they are unconscious, what makes more difficult to save them. Therefore, the capability and rapidity of disaster surviving victim positioning is the most critical for the survivor life saving.

Detection and positioning of human beings is very interesting also for military and security operations. Here, reservoirs, power plants, and other critical infrastructures are extremely vulnerable to terrorist attack. Therefore, the request for monitoring of these critical environments and for the detection of unauthorized intrusion is still needful. At these events, the knowledge about the number of persons and their position in the operational area can be very useful for military or security teams to take the right decisions. In the outlined disaster events and law enforcement operations the persons to be detected and localized are often situated behind an obstacle (e.g. wall, rubbles, snow, etc.). That is the reason why conventional optical and infrared sensors cannot be applied for human beings localization and tracking. Trained dogs, special cameras assigned for survivors searching under debris, acoustical sensors and through-the-obstacles seeing sensors can provide solutions of the outlined problem.

As through-the-obstacles seeing sensors, short-range high-resolution radars emitting electromagnetic waves with ultra-wide frequency band (UWB radars) using relatively low frequencies can be used with advantage. Here, the ultra-wide frequency band provides the fine resolution of the radar systems. On the other hand, the electromagnetic waves emitted in the frequency band DC-5GHz can penetrate through standard non-metallic materials (e.g. concrete, bricks, wood, etc.) with acceptable attenuation. Therefore UWB radars (sensors) exploiting this frequency band are capable to detect not only the targets located line-of-sight, but also the target situated behind a non-metallic obstacle. The power of the signal emitted by the mentioned UWB radars is above 10mW.Taking into account the outlined parameters, the key circuitry of the short-range through-the-obstacles seeing UWB radars can be implemented in a form of ASIC at acceptable size of radar antennas. Hence, the mentioned radars can be constructed to be light-weight and small-sized. And hence they could be available as handheld sensor systems consisting of antenna system, RF block, AD convertors, digital circuitry including a computer and software. The key part of the software consists in the implementation of UWB radar signal processing procedure intent on human being detection, localization and tracking. Our contribution will be devoted just to radar signal processing procedures and methods proper for the mentioned applications. Then, our contribution will have the following structures.

Firstly, we will introduce the basic model of raw radar signals obtained by the UWB sensors. Then, based on analyzes of the raw radar signal structure, we will present the basic procedures of radar signal processing to be used for person detection, localization and tracking. The mentioned procedures consist of the set of signal processing phases. Here, we will point out that the procedure structure (i.e. the sequence of the particular phases) depends on the type of the motion activities of the persons to be detected (e.g. walking, respiratory motion, motion of the particular limbs of persons, etc.). Then, it will be shown that the basic radar signal processing procedure for human being detection, localization and tracking consists of the phases such as raw radar signal preprocessing, background subtraction, time-of-arrival estimation, detection, localization and tracking. Each of these phases is implemented using proper signal processing methods. Depending on the scenario complexity, the fundamental procedure can be completed by additional phases. Therefore, we will present also these additional phases and some modifications of the fundamental radar signal procedure. A list of the signal processing methods applied within the particular procedures will be also given. The efficiency of the presented approach for human being detection, localization and tracking will be demonstrated by the results obtained at the measurement with the experimental UWB sensor systems. In the conclusion, a summary of challenging problems connected with detection, localization and tracking will be outlined.

Speaker bio:

Dušan Kocur was born in 1961 in Košice, Slovakia (in the past Czechoslovakia). He received the M.Sc., and Ph.D. degrees in radioelectronics from Technical University of Košice, Slovakia, in 1985 and 1991, respectively. From 1985, he has been with Technical University of Košice. From 2003, he has been in the position the full professor at the Department of Electronics and Multimedia Communication of his Alma Mater. From 2000 to 2007, he was the dean of the Faculty of Electrical Engineering and informatics of Technical University of Košice. From 2009 to 2013, he was the head of the Centre of Information and Communication Technologies for Knowledge Systems of Technical University of Košice. At the present time, Prof. Dušan Kocur gives the lectures on Linear Circuit Theory, Spread Spectrum Communication Systems and UWB Sensor Networks. In the field of research, his current study interests include UWB radar signal processing (human being detection, localization and tracking, static object imaging (UWB radar with synthetic aperture), UWB impedance spectroscopy, etc.), sensor networks (e.g. sensor network for water quality evaluation), wireless communication systems (physical layer of wireless communication systems, advanced base-band modulation schemes, multicarrier communication systems, spread spectrum communications, etc.) and their applications.

Important dates and deadlines:

February 1, 2015
Deadline extended to February 23, 2015 - Full paper submission

February 27, 2015
Deadline extended to March 15, 2015 - Acceptance notification

April 3, 2015 - Final paper submission & early payment

After April 3, 2015 - Late payment
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