# Fast Event-based Double Integral for Real-time Robotics

arXiv: https://arxiv.org/abs/2305.05925 · HTML: https://mlsanity.com/paper/2305.05925/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 May 2023.

## Built on by (most cited first, 7 of 7)

- [Dynamic EventNeRF: Reconstructing General Dynamic Scenes from Multi-view RGB and Event Streams](https://mlsanity.com/paper/2412.06770/) (2024)
- [An Event-based Fast Intensity Reconstruction Scheme for UAV Real-time Perception](https://mlsanity.com/paper/2508.02238/) (2025)
- [SpikeGS: Learning 3D Gaussian Fields from Continuous Spike Stream](https://mlsanity.com/paper/2409.15176/) (2024)
- [TAPFormer: Robust Arbitrary Point Tracking via Transient Asynchronous Fusion of Frames and Events](https://mlsanity.com/paper/2603.04989/) (2026)
- [EROAM: Event-based Camera Rotational Odometry and Mapping in Real-time](https://mlsanity.com/paper/2411.11004/) (2024)
- [Filter-Based Reconstruction of Images from Events](https://mlsanity.com/paper/2510.20071/) (2025)
- [Event-Based Motion Estimation via Oriented Distance Fields](https://mlsanity.com/paper/2608.24223/) (2026)

## Abstract (arXiv)

Motion deblurring is a critical ill-posed problem that is important in many vision-based robotics applications. The recently proposed event-based double integral (EDI) provides a theoretical framework for solving the deblurring problem with the event camera and generating clear images at high frame-rate. However, the original EDI is mainly designed for offline computation and does not support real-time requirement in many robotics applications. In this paper, we propose the fast EDI, an efficient implementation of EDI that can achieve real-time online computation on single-core CPU devices, which is common for physical robotic platforms used in practice. In experiments, our method can handle event rates at as high as 13 million event per second in a wide variety of challenging lighting conditions. We demonstrate the benefit on multiple downstream real-time applications, including localization, visual tag detection, and feature matching.