Fast Online 3D Reconstruction of Dynamic Scenes From Individual Single-Photon Detection Events

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Abstract

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 reliably 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.
Original languageEnglish
Pages (from-to)2666-2675
Number of pages10
JournalIEEE Transactions on Image Processing
Volume29
Early online date12 Nov 2019
DOIs
Publication statusPublished - 2020

Keywords

  • 3D reconstruction
  • Bayesian filtering
  • online estimation
  • single-photon Lidar

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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