CS-ORION
Compressed Sensing for Remote Imaging in Aerial and Terrestrial Surveillance
| Coordinatore | FOUNDATION FOR RESEARCH AND TECHNOLOGY HELLAS
Organization address
address: N PLASTIRA STR 100 contact info |
| Nazionalità Coordinatore | Greece [EL] |
| Totale costo | 1˙292˙270 € |
| EC contributo | 1˙292˙270 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2009-IAPP |
| Funding Scheme | MC-IAPP |
| Anno di inizio | 2010 |
| Periodo (anno-mese-giorno) | 2010-09-01 - 2014-08-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
FOUNDATION FOR RESEARCH AND TECHNOLOGY HELLAS
Organization address
address: N PLASTIRA STR 100 contact info |
EL (HERAKLION) | coordinator | 340˙748.00 |
| 2 |
COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
Organization address
address: RUE LEBLANC 25 contact info |
FR (PARIS 15) | participant | 393˙756.00 |
| 3 |
SAGEM DEFENSE SECURITE
Organization address
address: 18 AU 20 QUAI DU POINT DU JOUR contact info |
FR (BOULOGNE-BILLANCOURT) | participant | 320˙040.00 |
| 4 |
VIRTUAL TRIP LTD
Organization address
address: STREET 1770 10 contact info |
EL (HERAKLION) | participant | 237˙726.00 |
Mappa
Word cloud
Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.
Obiettivo del progetto (Objective)
'In this project, our focus is on the design, testing, and evaluation of compressive sensing (CS) architectures for enhancing the high-quality video acquisition and delivery capabilities of remote sensing devices that will enable them to provide efficient remote imaging in aerial and terrestrial surveillance. We will address limitations to current video coding methods which restrict the use of remote sensing devices to offering only a low-quality streaming video to the user. In order to overcome these limitations, novel algorithms which go well beyond the currently developed techniques and standards are needed. Equally importantly, the proposed methods must be developed with the hardware constraints of the platform of operation in mind, including restrictions regarding computational, memory, and power consumption, as well as the available reserved bandwidth. The proposed activities are designed in order to address these challenges. An important aspect of this project is the conscious exploitation of the inherent encryption of the signal that the compressive sensing methodology offers. We intend to use this property to enrich the signal intelligence capabilities of surveillance systems. The proposed consortium consists of partners with complementary expertise which covers all the involved research areas, from the point of capturing the video imaging content to the point that it is dynamically reconstructed and analyzed through CS reconstruction techniques by the user.'
Introduzione (Teaser)
The video quality of remote imaging used for monitoring and surveillance purposes is usually poor. An EU-funded project is coming up with creative and novel video compression techniques that enhance the definition without demanding greater space.
Descrizione progetto (Article)
Unmanned aerial vehicles (UAVs), terrestrial-based sensor networks and other remote-sensing technologies are increasingly used for civilian and military surveillance, reconnaissance and intelligence gathering. These systems have benefited from advances in communications and computing technology, which have lowered costs and boosted capabilities.
But technological progress does not stand still, and an EU-funded project is striving to take remote-sensing technology to the next level. The 'Compressed sensing for remote imaging in aerial and terrestrial surveillance' (CS-ORION) project is striving to overcome the limitations imposed by current video coding methods used by remote-sensing devices. Currently, these only offer the user low-quality streaming video.
The project is developing compressive sensing (CS) architectures that will provide high-quality video acquisition and delivery capabilities of remote-sensing devices for both aerial and terrestrial surveillance.
CS-ORION has designed a video compression technique able to overcome the limitations of mpeg and mjpeg compression. It combines a simplified encoding process with a refinement phase based on inter-frame prediction. The project has also developed and implemented a novel approach to video classification that directly exploits the properties of linear random projections in the framework of CS.
In addition, CS-ORION has created an active range imaging system that can reconstruct high-quality depth from significantly fewer frames. The project has also experimented with high-dynamic range imaging, which dramatically reduces the number of images required. Moreover, CS-ORION has used CS to perform accurate localisation based on signal strength measurements.
Once completed in the summer of 2014, CS-ORION will help advance the application of video imaging in transport, security and environmental monitoring.