PhDCurrent Audio-Video (A-V) players are limited to pausing, resuming, selecting and
viewing a single video stream of a live broadcast event that is orchestrated by a
professional director. The main objective of this research is to investigate how to create a
new custom-built interactive A V player that enables viewers to personalise their own
orchestrated views of live events from multiple simultaneous camera streams, via
interacting with tracked moving objects, being able to zoom in and out of targeted
objects, and being able to switch views based upon detected incidents in specific camera
views. This involves research and development of a personalisation framework to create
and maintain user profiles that are acquired implicitly and explicitly and modelling how
this framework supports an evaluation of the effectiveness and usability of
personalisation.
Personalisation is considered from both an application oriented and a quality supervision
oriented perspective within the proposed framework. Personalisation models can be
individually or collaboratively linked with specific personalisation usage scenarios. The
quality of different personalised interaction in terms of explicit evaluative metrics such as
scalability and consistency can be monitored and measured using specific evaluation
mechanisms.European Union's
Seventh Framework Programme ([FP7/2007-2013]) under grant agreement No. ICT-
215248 and from Queen Mary University of London
