A NEURAL ARCHITECTURE FOR VISUAL INFORMATION-PROCESSING

We report on the work done at the Institut fur Neuroinformatik in Bochum concerning the development of a neural architecture for the information processing of autonomous visually guided systems acting in a natural environment. Since biological systems like our brain are superior to artificial systems in solving such a task, we use findings from neurophysiology and -anatomy as well as psychophysics for defining processing principles and modules that have been implemented on our mobile platform MARVIN. MARVIN is equipped with an active stereo camera system. Our final objective is to define a neural instruction set for early information processing in the sense of a perception for action approach. From the biological paradigm we use principles like active vision, foveation, two-dimensional cortical layers, mapping, and discrete parametric representations in a task-oriented way to solve problems like obstacle avoidance, path planning, scene recognition, tracking, and 3D perception. This paper has the character of an overview of the work done in this field at our institute. Most of the modules presented here were published either in conference proceedings or in journals which will be referenced for a more thorough discussion of each issue.