A biologically inspired modular VLSI system for visual measurement of self-motion

We introduce a biologically inspired computational architecture for small-field detection and wide-field spatial integration of visual motion based on the general organizing principles of visual motion processing common to organisms from insects to primates. This highly parallel architecture begins with two-dimensional (2-D) image transduction and signal conditioning, performs small-field motion detection with a number of parallel motion arrays, and then spatially integrates the small-field motion units to synthesize units sensitive to complex wide-field patterns of visual motion. We present a theoretical analysis demonstrating the architecture's potential in discrimination of wide-field motion patterns such as those which might be generated by self-motion. A custom VLSI hardware implementation of this architecture is also described, incorporating both analog and digital circuitry. The individual custom VLSI elements are analyzed and characterized, and system-level test results demonstrate the ability of the system to selectively respond to certain motion patterns, such as those that might be encountered in self-motion, at the exclusion of others.