Live demonstration: Neuro-inspired system for realtime vision tilt correction

摘要

Correcting digital images tilt needs huge quantities of memory, high computational resources, and use to take a considerable amount of time. This demonstration shows how a spikes-based silicon retina dynamic vision sensor (DVS) tilt can corrected in real time using a commercial accelerometer. DVS output is a stream of spikes codified using the address-event representation (AER). Event-based processing is focused on change in real time DVS output addresses. Taking into account this DVS feature, we present an AER based layer able to correct in real time the DVS tilt, using a high speed algorithmic mapping layer and introducing a minimum latency in the system. A co-design platform (the AER-Robot platform), based into a Xilinx Spartan 3 FPGA and an 8051 USB microcontroller, has been used to implement the system.