Signal Processing Seminar

• Tuesday, 27 October 2015
• 16:00-16:45
• HB 17.150

Compressive Sensing-based Video Coding and Range Imaging Platforms

George Tzagkarakis
EONOS Investment Technologies (Paris, Fr.) and ICS-FO.R.T.H (Crete, Greece)

The framework of compressive sensing (CS), acting simultaneously as a sensing and compression protocol, has revolutionized the design of low-complexity onboard remote imaging devices with reduced power and processing requirements. This is achieved by reducing radically the sampling rates dictated by the well-established Shannon-Nyquist theory.

In this presentation, the core properties of CS will be exploited towards improving the performance of existing solutions in two distinct application areas of high industrial interest.

First, we will focus on the design of efficient lightweight video codecs to cope with the growing compression ratios required by modern remote imaging applications. To this end, appropriate CS modules are embedded in the typical MPEGx and M/JPEG systems to exploit frame sparsity in an appropriate residual and/or transform domain, with the main computational burden being put at the decoder, where increased computational and power resources are usually available.

The second application concerns the design of a CS-based methodology for range imaging using time-of-flight cameras, which aims at reducing dramatically the number of necessary frames for reconstructing the depth map of a scene. The use of CS in this case is motivated naturally by the inherent spatial sparsity of objects located in space.

For both application scenarios, we illustrate the effectiveness of CS in improving significantly the performance of previous approaches, thus making it a very promising solution for future high-performance systems.

About the presenter

Dr. G. Tzagkarakis received the Ph.D. and M.Sc. degrees (first in class, Honors) from the Computer Science Department ‐ University of Crete (UoC), Greece, and a B.Sc. degree in Mathematics from the Department of Mathematics (UoC) (first in class, Honors).

Since 2000 he has been also collaborating with the Wave Propagation Group of the Institute of Applied and Computational Mathematics (IACM)‐FO.R.T.H., while in 2002‐2010 he was affiliated as a research assistant in the Telecommunications and Networks Lab (TNL) of the Institute of Computer Science (ICS)‐FO.R.T.H. In the period 2010‐2012 he was a member of the Cosmology and Statistics Lab of CEA/Saclay as a Marie Curie post‐doctoral researcher focusing on the design and implementation of compressive sensing algorithms for remote imaging in areal and terrestrial surveillance systems.

From 2012, he holds a research associate position in EONOS Investment Technologies, working on the development of statistical signal processing algorithms with applications in computational finance and econometrics, while in parallel he is a research collaborator with the Signal Processing Lab (SPL) at ICS‐FO.R.T.H.

His research interests lie in the fields of statistical signal and image processing, with emphasis in non‐Gaussian heavy‐tailed modeling, compressive sensing and sparse representations, with applications in signal processing, image and video processing, and computational finance. Among his topics of interest are also distributed signal processing for sensor networks, information theory, image classification and retrieval, and inverse problems in underwater acoustics.

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Overview of Signal Processing Seminar