A Bio-Inspired Neuromorphic Active Vision System Based on Fixational Eye Movements

Similar to biological retinas, neuromorphic Dynamic Vision Sensor (DVS) devices only respond to changes in the visual scene. It has been observed that in biological systems there is a causal relationship between fixational eye movements and target visibility during fixation, which plays a central role in vision. Based on these findings we implemented an active vision system comprising of a DVS mounted on a pan-tilt unit to introduce microscopic and erratic camera movements as a pivot for artificial vision of static scenes. The key principle is that moving the sensor over an image shifts the low temporal frequency power of a static scene into a range that an event-based retina can properly signal and encode it as highly synchronous activity. By characterizing the signal provided by the active vision system we evidenced (1) an amplification of its response to high spatial frequencies; (2) a whitening effect when scaling stimulus contrast to match the structure of natural images; and (3) an equalized response to all possible orientations of static stimuli related to the isotropic statistics of the random-like motion. The design of a further proper anisotropic spatial summation of events with opponent contrast polarity in a biologically-realistic spiking neural network allowed the detection of information relative to the local orientation of stimuli in a fully bio-inspired fashion. We validate the system proposed with experimental results using synthetic control stimuli.