Neuromorphic Vision Systems for Mobile Applications

Abstract

Neuromorphic vision systems are ideal for mobile applications because they promise compact computational sensing at lower power consumption compared to the traditional imager/ADC/CPU systems. These properties are particularly important for unmanned aerial vehicles. We present current-mode low noise imaging, which is typically difficult to realize, and computation-on-readout imaging processing for stereopsis and motion estimation. We discuss how these processed images can be used for guiding and controlling an autonomous aerial vehicle