A Prototyping Environment for Integrated Artificial Attention Systems

Abstract

Artificial visual attention systems aim to support technical systems in visual tasks by applying the concepts of selective attention observed in humans and other animals. Such systems are typically evaluated against ground truth obtained from human gaze-data or manually annotated test images. When applied to robotics, the systems are required to be adaptable to the target system. Here, we describe a flexible environment based on a robotic middleware layer allowing the development and testing of attention-guided vision systems. In such a framework, the systems can be tested with input from various sources, different attention algorithms at the core, and diverse subsequent tasks.