Project Proposal (PDF) - Oxford Brookes University

FP7-ICT-2011-9 STREP proposal
18/01/12 v1 [Dynact]
the level of individual partners and as a whole;
represents a collection of widely complementary expertises, but at the same time is run by
individuals who have multi-disciplinary scientific background in many or all the fields involved.
2.3.3 Suitability and commitment to the tasks assigned
In virtue of its background illustrated above, the Oxford Brookes Vision Group (OBU) is obviosly extremely
well placed to tackle the tasks assigned to it by the project proposed here:
identification and classification of dynamical models for action recognition, in particular via metric
learning approaches (WP2);
learning and classification of novel dynamical discriminative models (WP3);
gathering a corpus of range/stereo videos of actions and gesture in various scenarios (WP4);
selection and extraction of features from both range cameras and traditional video (WP4);
application and validation in a variety of different scenarios (WP5).
SYSTeMS and IDSIA are two of the top European groups in Imprecise Probabilities and related theories.
Their pioneering work on imprecise (robust) graphical models and the generalisation of the Expectation
Maximisation algorithm to convex sets of probabilities is at the current edge of the research in the field.
Clearly, it is difficult to think of other research groups in Europe more suitable than SYSTeMS and IDSIA to
the crucial tasks assigned to them by the present project:
imprecise EM and its application to hidden Markov models (WP1);
imprecise Markov models and general imprecise graphical models (WP1);
the classification of imprecise graphical models (WP2).
There is in fact a partial overlap between the skills of these two partners, which are both engaged in
theoretical research about imprecise probabilities and graphical models. The level of ambition of the project
in this area, however (just think of the formulation of a general theory of imprecise graphical models),
simply requires the combined effort of two different partners. The ongoing fruitful interaction between the
two groups (which have a long tradition of joint works) is certainly going to facilitate a fast and satisfactory
achievement of the required tasks.
Supélec and DYNAMIXYZ, besides adding their own specific value to the consortium, form another couple
of closely linked partners, with a long record of close and fruitful collaboration in the field of virtual
animation and the use and commercialisation of active appearance models in the entertainment industry. As a
results, they have won prizes for gesture recognition challenges and established a network of commercial
contacts which will be invaluable for this project. They are therefore excellently placed to tackle:
the capturing of novel testbeds via range cameras for the gaming and animations scenarios (WP4);
the generation of realistic virtual clones of actors with a specific style (WP5); and
the recognition of facial expression (WP5).
2.3.4 Complementarity between partecipants and overall balance
A clear complementarity emerges between the five partners involved in this proposal. IDSIA and SYSTeMS
are world leaders on imprecise dynamical models and imprecise probabilities at large. OBU is world leader
in computer vision and machine learning, including the target fields of the present proposal: action and
gesture recognition, identity recognition from gait. OBU can bring valuable existing infrastructure to the
consortium, including range cameras, motion capture devices, computer clusters, and the equipment
provided by its Intelligent Transport Systems doctoral programme. The Coordinator is a leading researcher in
imprecise probabilities, while both OBU and Supélec/DYNAMIXYZ can provide their industrial expertise
and relations, together with the infrastructure necessary for prototype implementation in the manifold
scenarios identified by this project. OBU can further support the project via its wealth of industrial
connections with world class companies in the field, while IDSIA and SYSTeMS are at the center of the
academic community of imprecise probabilities. All partners have extensive networks of collaborations.
As a result, we believe, the consortium is carefully designed and quite well balanced, with respect to the
objectives of the project stated in Section 1.1, providing a good mix of expertises and backgrounds, both
academic and industrial, in the proportions necessary to ensure the success of the project.
Proposal Part B: page [48] of [67]