# Fast online 3D reconstruction of dynamic scenes from individual single-photon detection events

arXiv: https://arxiv.org/abs/1905.02944 · HTML: https://mlsanity.com/paper/1905.02944/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 May 2019.

## Built on by (most cited first, 1 of 1)

- [Joint Depth and Reflectivity Estimation using Single-Photon LiDAR](https://mlsanity.com/paper/2505.13250/) (2025)

## Abstract (arXiv)

In this paper, we present an algorithm for online 3D reconstruction of dynamic scenes using individual times of arrival (ToA) of photons recorded by single-photon detector arrays. One of the main challenges in 3D imaging using single-photon Lidar is the integration time required to build ToA histograms and reconstruct reliable 3D profiles in the presence of non-negligible ambient illumination. This long integration time also prevents the analysis of rapid dynamic scenes using existing techniques. We propose a new method which does not rely on the construction of ToA histograms but allows, for the first time, individual detection events to be processed online, in a parallel manner in different pixels, while accounting for the intrinsic spatiotemporal structure of dynamic scenes. Adopting a Bayesian approach, a Bayesian model is constructed to capture the dynamics of the 3D profile and an approximate inference scheme based on assumed density filtering is proposed, yielding a fast and robust reconstruction algorithm able to process efficiently thousands to millions of frames, as usually recorded using single-photon detectors. The performance of the proposed method, able to process hundreds of frames per second, is assessed using a series of experiments conducted with static and dynamic 3D scenes and the results obtained pave the way to a new family of real-time 3D reconstruction solutions.