Project Proposal (PDF) - Oxford Brookes University

FP7-ICT-2011-9 STREP proposal
18/01/12 v1 [Dynact]
Section 3. Impact
3.1 Expected impacts listed in the work programme
3.1.1 Connection with expected impacts in the work programme.
The expected impacts listed in the work programme in relation to Objective 2.1: Cognitive Systems and
Robotics are the following:
“Integrated and consolidated scientific foundations for engineering cognitive systems under a variety
of physical instantiations.”
Giving its breakthrough nature, and the position of its partners at the top of the respective scientific
disciplines, the proposed project is clearly designed to consolidate the scientific foundations within
Europe and at worldwide level in a number of key topics of cognitive systems: generative and
discriminative learning from labelled training sets, the formulation of novel frameworks for robust
action recognition; their testing and application to the variety of physical, societal and industrial
scenarios depicted in Section 1.1.
Actions to undertake: this outcome will be a natural consequence of the successful conclusion of the
project. An appropriate publication strategy will be crucial in this respect. We will also explore, in
the likely case of success, the opportunity of engaging other academic partners in follow-up research
projects addressing the further extension and consolidation of the results obtained: for instance, we
see scope for more focussed, dedicated projects on manifold learning and discriminative modelling,
and wider (possibly IP) projects on the integration between vision and robotics (in terms of both
terrestrial and aerial vehicles), building on our existing record in autonomous navigation.
“Significant increase in the quality of service of such systems and of their sustainability in terms of,
for instance, energy consumption, usability and serviceability, through the integration of cognitive
capabilities.”
An intelligent use of the proposed techniques has the potential to contribute to energy saving and
environmental protection. In surveillance, for instance, automatic event recognition could lead to
more efficient security approaches in which humans do have to waste their time for long hours in
front of static scenes, but are only alerted when some unusual activity is actually taking place.
Efficient tools for gesture recognition can help much in supporting disabled or elderly people, much
improving their quality of life. In video data retrieval, manual search could be significantly sped up
using automatic retrieval techniques, resulting in both energy saving and increased productivity in
the high-tech commercial sectors involved. As a general remark, efficient automatic or semiautomatic
(with human assistance) action recognition has enormous potential for improving the
competitiveness of European players in all involved scenarios, via significant gains in productivity.
“Innovation capacity in a wide range of application domains through the integration of cognitive
capabilities.”
The huge number of scenarios in which the need for robust action and activity recognition arise have
been widely discussed when introducing and motivating the problem: they are reflected in the tasks
the central work package 5 is articulated into: gait identification, entertainment and interactive video
games, video retrieval over the internet, autonomous navigation, animation and facial expression
analysis.
In all these scenarios (and in many others which we mentioned but could not include here for sheer
lack of time and resources, think for instance of human computer interaction, smart homes, and
semi-automatic care for the elderly) a successful outcome of this project will contribute enormously
in terms of both cutting-edge innovation and economic boost for the economic and societal sectors
involved, all the more crucial in times of economic uncertainty and recession.
Companies like Google are heavily investing on video data mining; Street View is just an example
Proposal Part B: page [51] of [67]