Stochastic image processing and simultaneous dewarping for aerial vehicles

Abstract

There is increasing interest for aerial vehicles to perform image processing tasks (i.e. object recognition and detection) in real-time. Such systems systems should have minimal data throughput, low computational complexity, and low-power. Traditional frame-based digital cameras are not ideal for meeting such specifications. More recent cameras, inspired by biology, drastically reduce data throughput by representing information in event streams, and in doing so, represent image information temporally. In this work, we utilize the ATIS (Asynchronous Time-based Image Sensor) in conjunction with a Field-Programmable Gate Array implementation of the Integrate-and-Fire Array Transceiver for performing an event-based, simultaneous image dewarping and filtering task. The ATIS output is inherently event-based and stochastic, giving our system the low data throughput and low-power specifications that we seek, as it more directly mimics the communication protocol of biological neurons. We further emphasize how our system can be coupled with aerial vehicles that must perform visual tasks in real-time on a coherent representation of what its camera has captured.