Advances in data processing and machine learning in camera networks

Hichem Snoussi (Prof. à l'université de technologique de Troyes)
July 09, 2019 — 15:30 — "Amphitéatre Janet (bât. Breguet)"

Abstract

The aim of this tutorial is to give an overview of recent advances in distributed signal/image processing in wireless sensor networks. Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena and for target tracking in a wide region or a critical infrastructure under surveillance. With such systems, the automatic monitoring of an event or an incident is based on the reliability of the network to provide an efficient and robust decision-making. Applying conventional signal/image techniques for distributed information processing is inappropriate for wireless sensor networks, since the computational complexity scales badly with the number of available sensors and their limited energy/memory resources. For this purpose, collaborative information processing in sensor networks is becoming a very attractive field of research. The sensors have the ability to collaborate and exchange information to ensure an optimal decision-making. In this tutorial, we review recently proposed collaborative strategies for self-localization, target tracking and nonlinear functional estimation (nonlinear regression), in a distributed wireless sensor network. The collaborative strategy ensures the efficiency and the robustness of the data processing, while limiting the required communication bandwidth. Signal processing challenges in mobile ad-hoc sensor networks will also be considered in this tutorial.

Biography

Hichem Snoussi received the diploma degree in Electrical Engineering from the Ecole Superieure d’Electricite (Supélec), Gif-sur-Yvette, France, in 2000. He also received the DEA degree and the Ph.D. in signal processing from the University of Paris-Sud, Orsay, France, in 2000 and 2003 respectively. Between 2003 and 2004, he was postdoctoral researcher at IRCCyN, Institut de Recherches en Communications et Cybernétiques de Nantes. He has spent short periods as visiting scientist at the Brain Science Institute, RIKEN, Japan and Olin Neuropsychiatry Research Center at the Institute of Living in USA. Between 2005 and 2009, he was associate professor at the University of Technology of Troyes, France. He has obtained the HDR degree from the University of Technology of Compiègne in 2009. Since 2010, he is Full Professor at the University of Technology of Troyes. His research interests include Bayesian techniques for source separation, information geometry, differential geometry, machine learning, robust statistics, with application to brain signal processing, astrophysics, advanced collaborative signal/image processing techniques in wireless sensor/cameras networks, nuclear source detection, geolocalization and tracking, security and surveillance,… Since 2010, he has been in charge of the CapSec plateform (Sensors for Security). He is the principal investigator of many ANR projects and industrial partnerships. In 2009, he launched a new company Track&Catch on smart embedded cameras for security and surveillance, where he is the scientific director. In 2014, he co-founded an innovative company Damavan Imaging on cutting-edge novel Gamma ray detectors for PET imaging and Compton cameras for nuclear source reconstruction.