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

Yoann Altmann, Stephen McLaughlin, Michael Davies

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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
JournalIEEE Transactions on Image Processing
Early online date12 Nov 2019
Publication statusE-pub ahead of print - 12 Nov 2019


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