GPU-accelerated affordance cueing based on visual attention

This work focuses on the relevance of visual attention in affordance-inspired robotics. Among all approaches in robotics related to Gibson\´s concept of affordances the dealing with attention cues is only rudimentary. We are introducing this concept within the perception layer of our affordance-inspired robotic framework. In this context we present a high-performance visual attention system handling invariants in the optical array. This layer builds the base of higher-sophisticated tasks, like a "curiosity drive" that helps a robotic agent to explore its environment. Our attention system derived from VOCUS utilizes the parallel design of the graphics processing unit (GPU) and reaches real-time performance for the processing of online video streams in VGA resolution on a single computer platform. GPU-VOCUS is currently the fastest known visual attention system running on standard personal computers.