An intelligent cognitive vision
platform is a scene understanding system with a full degree of autonomy to adapt
itself to new situations, with high interaction capabilities using a friendly
language to understand user needs and
with various ways to communicate its understanding of the observed
scenes.
2.1
Autonomy
The intelligent cognitive vision
platform will have autonomy capabilities in two different modes: static
configuration or dynamic reconfiguration. In a configuration phase the platform
can select automatically pertinent vision algorithms from a library of
programmes and can process data coming from a set of heteregenous sensors in a
plug and play manner. This feature is mandatory for easy passage from one
application to another or from one site to another. In a dynamic reconfiguration
phase the platform must adapt itself in real-time. This feature is mandatory for
robustness purposes when working 7 days a week 24 hours a
day.
2.2
Interactivity
The intelligent cognitive vision
platform will be able to adapt its behaviour directly by taking into account
end-user specifications. In particular a high level language based on an
ontology will allow to describe new classes of objects, new events or new
complex activities.
2.3
Communication
The intelligent cognitive vision
platform must have scalable visualization tools ranging from very simple palm
pilot display to immersive
environments, real time transmission of pertinent data and complex image/video annotation for
archiving.
This objective is very ambitious,
however current state of the art techniques in cognitive vision have shown that
they can propose partial solutions.
There is a need to gather the best techniques in a unique framework and to
define standards. The following research activities must be performed to reach
this objective:
3.1 To build a standard state of
the art vision library
3.2 Program supervision
techniques
3.3 Real time spatio-temporal
reasoning
3.4 Ontology of visual
concepts
3.5 High level language for
end-user specification
3.6 Learning
3.7 Simulation
techniques
This platform will be a solution
for several challenging applications. Among them we can cite smart environments,
visual surveillance and virtual teacher.
This ambitious objective is by
definition a way to federate cognitive vision research and to concretize the
results in a common platform to show that cognitive vision works effectively and
allow to start a new generation of vision systems.