Activity Analysis

Our research on activity analysis from video has focussed largely on human behaviour. We are interested in all aspects of this problem, including fundamental research on categorisation, tracking, segmentation and motion modelling, through to applied work addressing social and commercial priorities. Some of our recent work, in collaboration with the School's KRR group, is exploring the integration of vision within a broader cognitive framework, including audition, inductive reasoning, and intentionality.

	Bicycle theft detection Recognising drop and pick events and linking related events applied to bicycles. This method could assist raising a warning when the person picking the bicycle does not 'look like' the person who dropped it
	Learning activities from video Learn about the activities within a scene, and then about the objects involved in these activities
	Detecting carried objects Detect large objects (e.g. bags) carried by pedestrians depicted in short video sequences
	Motion segmentation by consensus Segment moving objects from tracked features
	Learning to play table-top games Learn about the objects and patterns of moves used in simple table-top games, and then apply these to play the game
	Modelling the intentions of pedestrians Detect atypical pedestrian trajectories, assuming a simple model of goal-directed navigational behaviour
	Watermark extraction Localise paper-based watermarks using image processing

Earlier work - but still of interest...

	Tracking A generic object tracker, developed initially for tracking vehicles
	Music via Motion Create an augmented and interactive audio-visual space
	Soccer Tracking Tracking the movements of individual players in team games
	Temporal Continuity Enforcing global spatio-temporal consistency to enhance reliability of moving object tracking and classification
	Traffic Interactions Modelling traffic interaction using learnt qualitative spatio-temporal relations and variable length Markov models
	Synthetic Interaction Synthesise an interactive agent by learning from the interactive behaviour of people
	Electronic stockman's eye Tracking cows and looking for abnormalities in their movements
	VLMMs of behaviour Learning variable length markov models of human behaviour
	IMV Detecting unusual events by modelling simple interactions between people and vehicles
	OMR Optical music recognition (with dept. of music)
	Behaviour modelling Modelling of `object behaviours' using detailed, learnt statistical models
	Hand tracking Robust, model-based methods for tracking deformable objects
	Pedestrian tracking Contour tracking using Active Shape Models. Source code for the Baumberg tracker.