Mind-Reading Computer
Drawing inspiration from psychology, computer vision and
machine learning, the team in the Computer Laboratory at the University of
Cambridge has developed mind-reading machines — computers that
implement a computational model of mind-reading to infer mental states of
people from their facial signals. The goal is to enhance human-computer
interaction through empathic responses, to improve the productivity of the user
and to enable applications to initiate interactions with and on behalf of the
user, without waiting for explicit input from that user.
There are difficult
challenges:
Using a digital video camera, the mind-reading computer
ppt system analyzes a person's facial expressions in real time and
infers that person's underlying mental state, such as whether he or she is
agreeing or disagreeing, interested or bored, thinking or confused.
Prior knowledge of how particular mental states are expressed
in the face is combined with analysis of facial expressions and head gestures
occurring in real time. The model represents these at different granularities,
starting with face and head movements and building those in time and in space
to form a clearer model of what mental state is being represented.
Software from Nevenvision identifies 24 feature points on the face and tracks them in real time. Movement, shape and colour are then analyzed to identify gestures like a smile or eyebrows being raised. Combinations of these occurring over time indicate mental states. For example, a combination of a head nod, with a smile and eyebrows raised might mean interest. The relationship between observable head and facial displays and the corresponding hidden mental states over time is modeled using Dynamic Bayesian Networks.
Software from Nevenvision identifies 24 feature points on the face and tracks them in real time. Movement, shape and colour are then analyzed to identify gestures like a smile or eyebrows being raised. Combinations of these occurring over time indicate mental states. For example, a combination of a head nod, with a smile and eyebrows raised might mean interest. The relationship between observable head and facial displays and the corresponding hidden mental states over time is modeled using Dynamic Bayesian Networks.
You can download Mind-Reading Computer seminar abstract from here.
0 comments:
Post a Comment