A visual attention model for tracking regions based on color correlograms

The amount of information contained in a single color shot of a scene is extreme considering the variety of tasks that can be performed relying on visual data only. For the purpose of analyzing scenes dynamically, where objects come and go, one has to work under a structure of a visual attention model which prioritizes what type of visual data the system has to follow. This paper presents a novel visual attention model for region tracking based on color correlograms. First, a reference frame is picked and it is segmented for the most significant color regions present in the shot. Color correlograms are then run on every frame after in order to provide spectral and spatial information, for the visual attention control, about the past and the new objects appearing on the scenes. The visual attention (VA) model then keeps track of old and new color regions appearing on the scene until a different frame is chosen. We have run experiments which show the performance of this proposed VA model.