EYE2E: Building visual brain for fast human machine interaction
EYE2E is an FP7 project (2011-2015).
The primary objective of this project is to build international capacity and cooperation in the field of
biologically inspired visual neural systems, via software simulation and hardware realization, with an
application focus on fast human-machine interaction.
Effective computer vision is a major research challenge. Vision plays a critical role in the interaction of
most animal species with a dynamic world, and even relatively low order animals have remarkable
visual processing capabilities. For example, insects can respond to approaching predators with
remarkable speed. Recent research demonstrates that modelling biologically plausible artificial visual
neural systems can provide new solutions for computer vision in dynamic environments. In particular,
human-machine interaction is a rich domain demanding improved machine perception, with the potential
for huge impact in a range of applications, such as intelligent robots, surveillance and video games.
However, much research in neural vision has been based upon general computing systems, whereas
the powerful parallel computing capacity of visual neural systems can only be fully demonstrated and
utilized when realized in Very Large Scale Integrated (VLSI) chips.
Focusing on modelling biological visual neural systems and realizing them in chips for human-machine
interaction, the research staff exchange programme will bring opportunities for the four partners to work
together and complement each others’ research strengths via research staff secondments, training
seminars, joint workshops and jointly organised conferences, to explore the multidisciplinary research
area and to build strong connections between the European institutions and partner institutions in a fast
growing economy.
Five work packages (WPs) are designed to achieve the objectives of the project, i.e., biological plausible
visual neural system modelling, multiple visual neural systems integration, VLSI neural vision chip
design, biologically plausible vision systems for human-machine interaction, and management,
networking and dissemination.
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Dr. John Muarry visited Tsinghua University, and gave a talk on his research.
PhD student Farshad Arvin is there as well on his secondment. 
EYE2E Lincoln site training seminar 1/CIL methods meeting,
11:00-15:15@MC3108 MHAT Building, Friday,18/05/2012, lunch@Barge