Detection and localization of objects in time-varying imagery using attention, representation and memory pyramids

摘要

This paper describes a novel approach in target recognition, using active and selective perception and perceptual learning in the analysis of time-varying imagery. Attention mechanisms are implemented through the use of three linked functional pyramids corresponding to image representation, memory, and attention. Multiresolution search, supported by saccade and zoom-lens control, allows a system's focus of attention to roam inside an image pyramid under the guidance of an attention pyramid and analyse a field-of-view at any available resolution. Simulations showed this approach reducing the volume of data to be processed and performing robustly as characterized by the absence of false negatives and the presence of very few false positives.