I am a member of both the Departmental computer vision and interaction, media and communications research groups
One of the accepted Grand
Challenges of science is to understand the workings of the human brain. This is
a problem that has many aspects and many levels, but one of the most promising
is to study the brain as a computational system, and in particular to study the
lower level processing components, such as early vision and sensory-motor
integration which are both experimentally accessible and lend themselves to
algorithmic description. The development of such biologically validated
algorithms also allows their transfer to build functional computer artefacts
mimicking natural behaviours and supporting new forms of human computer
interactions.
My work on early visual
processing over the past 13 years has shown that a single gradient-based
mechanism can account for a range of visual phenomena that were previously
attributed to separate neural mechanisms. This computational framework has been
psychophysically validated and has lead to the discovery of a number of new
visual illusions. This gradient approach has been shown to transfer between
visual sub-domains, motion and spatial orientation to date, so providing a
contended for a generalised framework for understanding human visual
processing. The algorithms developed have then been used to develop robust real
time computer vision systems to extract important scene properties such as
optical flow and slope.
My work on sensory motor integration examined initially a novel insect behaviour, active motion camouflage, and developed the first explicit neural model for this stealth strategy. Using the model developed it was possible to incorporate it into a virtual environment and show for the first time that humans are also susceptible to this camouflaging behaviour. Examination of human sensory motor performance also allowed the development of an award winning Internet based security system using computer mouse based signatures, which we showed for the first time to be both reproducible and biometric.
Closing the perception action
loop in human computer interaction is an extension and integration of this
previous work, using biologically inspired methods and computer vision
techniques to develop systems capable of tracking faces, recognising facial
expressions and so supporting affective computing applications. This work is
extending currently to include the automated recovery of body language in an
effort to improve interaction. Through such systems we can attempt in the near
future to understand many of the higher-level cognitive processes in the human
brain concerned with affective communications, social intelligence and empathy.
Research on understanding the brain and the development of
artificial intelligence has been identified by the UK Government as an issue
that the public have concerns about. Key to the future acceptability of such
systems, and continued funding from the public purse of research, is the need
for public dialogue on the issues surrounding artificial intelligences.
Integral to my research agenda is a successful and ongoing engagement with the
public and media to demystify the subject and inspire the next generation of
researchers. An example being my collaborative Sodarace project, which was
selected for the Royal Society Summer Exhibition 2005 and the cs4fn project.
A full list of my grants held can be found here broken down across my work on computer vision and the interaction media and communications groups
Full list of my publications can be found here
1997 -2000 BBSRC/EPSRC Mathematical
Biology Initiative Project Grant A DIFFERENTIAL FORMS APPROACH TO MODELLING OPTIC FLOW
1999-2002 EPSRC Project Grant. EVOLUTION OF SENSORIMOTOR NEURAL NETWORKS TO PERFORM ACTIVE MOTION
CAMOUFLAGE