The main objective is to develop the theory of context-aware visual recognition systems. We will implement the theory in a complete closed-loop vision system, and apply it to two applications (city street surveillance and customer behaviour analysis). To achieve these objectives, we will develop new feature grouping, attention and appearance-based recognition processes. This will also require development of new techniques for acquiring, representing and using visual context and situation knowledge.

The work developed consisted mainly in two main areas:
– The use of Gabor filters for the detection of interest points and for the the representation of local image regions for posterior recognition.
– Feature selection and classifier design for the recognition of human activities from video.