An Event-based Fast Intensity Reconstruction Scheme for UAV Real-time Perception

TL;DR

This paper introduces a fast, efficient event-based intensity reconstruction method called ESI for UAV perception, enabling real-time high-quality imaging in challenging conditions with low computational load.

Contribution

The paper presents ESI, a novel single integration scheme that improves real-time intensity reconstruction from event streams, suitable for UAV onboard perception.

Findings

ESI achieves 100 FPS in intensity reconstruction.

ESI outperforms state-of-the-art algorithms in runtime efficiency.

ESI maintains high reconstruction quality in low-light UAV scenarios.

Abstract

Event cameras offer significant advantages, including a wide dynamic range, high temporal resolution, and immunity to motion blur, making them highly promising for addressing challenging visual conditions. Extracting and utilizing effective information from asynchronous event streams is essential for the onboard implementation of event cameras. In this paper, we propose a streamlined event-based intensity reconstruction scheme, event-based single integration (ESI), to address such implementation challenges. This method guarantees the portability of conventional frame-based vision methods to event-based scenarios and maintains the intrinsic advantages of event cameras. The ESI approach reconstructs intensity images by performing a single integration of the event streams combined with an enhanced decay algorithm. Such a method enables real-time intensity reconstruction at a high frame rate, typically 100 FPS. Furthermore, the relatively low computation load of ESI fits onboard implementation suitably, such as in UAV-based visual tracking scenarios. Extensive experiments have been conducted to evaluate the performance comparison of ESI and state-of-the-art algorithms. Compared to state-of-the-art algorithms, ESI demonstrates remarkable runtime efficiency improvements, superior reconstruction quality, and a high frame rate. As a result, ESI enhances UAV onboard perception significantly under visual adversary surroundings. In-flight tests, ESI demonstrates effective performance for UAV onboard visual tracking under extremely low illumination conditions(2-10lux), whereas other comparative algorithms fail due to insufficient frame rate, poor image quality, or limited real-time performance.