A new memory model for selective perception systems

Selectively perceiving systems explore their environment by fixating on and analyzing potentially interesting parts of a scene in a continual manner. During this process, a sequence of snapshots each containing visual data with distinct spatio-temporal properties is collected. In this paper, we propose a visual memory model that enables the integration of this spatio-temporal data. This memory model referred to as the bubble model uses a spherical surface attached to the viewpoint in order to store and manipulate information collected during selective perception process. The bubble surface can be deformed by a number of control points to represent visual information obtained from different fixation points. Bubbles are indexed by the viewpoint vectors so that they can be recalled or updated as necessary. Different bubbles attached to the same viewpoint can store multiple simple and complex features. Using time stamps and parametric surface representations the model can also be used to extract changes and similarities in the environment.