HERMES concentrates on how to
extract descriptions of human behavior from videos in a restricted
discourse domain, transform this into written text, and allow to
synthesis a dynamic scene based on a textual description. Discourse
domains are for example pedestrians crossing inner-city roads and
pedestrians approaching or waiting at stops of buses or trams. These
discourse domains allow to explore a coherent evaluation of human
movements and facial expressions across a wide variation of scale. This
general approach lends itself to various cognitive surveillance
scenarios at varying degrees of resolution: from wide-field-of-view
multiple-agent scenes, through to more specific inferences of emotional
state that could be elicited from high resolution imagery of faces.
HERMES aim to consider how cooperating pan-tilt-zoom sensors can
enhance the process of cognition via controlled responses to uncertain
or ambiguous interpretations. The system will be exposed to video
recordings from different parts of Europe in order to prevent over
adaptation to local habits and, in addition, to learn
systematically occurring differences between pedestrian habits in
different countries. The system's explanatory and arguing capabilities
are expected to ease an assessment of its strengths and weaknesses.
(short project presentations: NOV05 APR06)
(short project presentations: NOV05 APR06)