Towards a real-time framework for visual monitoring tasks

This work describes an active vision framework that is able to perform visual monitoring tasks involving attention control and pattern categorization behaviors. We use an articulated stereo vision platform and image processing device, which provides abstracted information about the environment. As a practical result of this work, the system can select a region of interest in its environment, perform attention shifts involving saccadic movements, and perform an efficient feature extraction and recognition. Also, attentional maps of the scene are incrementally constructed, and the maps are kept consistent with a current perception of the world. Another important result for the attentional mechanism is that the system is capable of analyzing all regions of its world, selected according to salience maps