Real-Time High-Performance Attention Focusing for Outdoors Mobile Beobots

Intelligent Distributed and Embedded Systems

Volume

Papers from the 2002 AAAI Spring Symposium

Contents

We describe a neuromorphic model of how our visual attention is attracted towards conspicuous locations in a visual scene. It replicates processing in posterior parietal cortex and other brain areas along the dorsal visual stream in the primate brain. The model includes a bottom-up (image-based) computation of low-level color, intensity, orientation and motion features, as well as a non-linear spatial competition which enhances salient locations in each of these feature channels. All feature channels feed into a unique scalar "saliency map" which controls where to next focus attention onto. Because it includes a detailed low-level vision front-end, the model has been applied not only to laboratory stimuli, but also to a wide variety of natural scenes. In addition to predicting a wealth of psychophysical experiments, the model demonstrated remarkable performance at detecting salient objects in outdoors imagery -- sometimes exceeding human performance -- despite wide variations in imaging conditions, targets to be detected, and environments.