Ziel
This project is about transferring knowledge of image and video forensics between the academia and industry. Building on the complementary expertise of the participants, the consortium aims to pursue two major lines of investigations: Device fingerprint based forensics and hidden data based forensics. The first line of investigation requires the formulation of a set of “fingerprint” left in the images/video by the hardware components or in-built signal processing algorithms of the imaging device and involves the study of its forensic applications. The applications we are aiming for include device identification, technology/licensing infringement detection, device linking, automatic media classification, tampering detection. To guarantee the value of the these techniques, anti-anti-forensics measures will also be devised to detect/prevent removal or substitution of the fingerprint set. The second line of investigation is about the use and analysis of hidden data in the host image/video for authentication, content integrity verification, copyright protection (including ownership identification, proof of ownership, copy control, traitor tracing), and the use and detection of covert communications. Although data hiding is a relatively mature research area, their applicability in the real world is yet to be fully explored due to the fact that the security issues are often interleaved with multimedia processing issues and requires addressing. Therefore this line of research requires the formulation of specific security requirements and attack modelling for specific applications. Overall, both lines of research require a wide variety of expertise such as multimedia signal processing, computer vision, pattern recognition, machine learning, and optimisation theory. Therefore it is expected that this project will also take the soundness and applicability of these theories to a new level and lay a solid foundation for wider lasting collaborations in the related areas.
Wissenschaftliches Gebiet
- social sciencesmedia and communicationsgraphic design
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsignal processing
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- natural sciencescomputer and information sciencesartificial intelligencepattern recognition
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Thema/Themen
Aufforderung zur Vorschlagseinreichung
FP7-PEOPLE-2009-IAPP
Andere Projekte für diesen Aufruf anzeigen
Finanzierungsplan
MC-IAPP - Industry-Academia Partnerships and Pathways (IAPP)Koordinator
CV4 8UW COVENTRY
Vereinigtes Königreich