Fast surface detection in single-photon Lidar waveforms

Julián Tachella, Yoann Altmann, Jean-Yves Tourneret, Stephen McLaughlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Single-photon light detection and ranging (Lidar) devices can be used to obtain range and reflectivity information from 3D scenes. However, reconstructing the 3D surfaces from the raw waveforms can be very challenging, in particular when the number of spurious background detections is large compared to the number of signal detections. This paper introduces a new and fast detection algorithm, which can be used to assess the presence of objects/surfaces in each waveform, allowing only the histograms where the imaged surfaces are present to be further processed. The method is compared to state- of-the-art 3D reconstruction methods using synthetic and real single-photon data and the results illustrate its benefits for fast and robust target detection using single-photon data.
Original languageEnglish
Title of host publication2019 27th European Signal Processing Conference (EUSIPCO)
PublisherIEEE
ISBN (Electronic)9789082797039
DOIs
Publication statusPublished - 18 Nov 2019
Event27th European Signal Processing Conference 2019 - A Coruna, Spain, A Coruna, Spain
Duration: 2 Sep 20197 Sep 2019
http://eusipco2019.org/

Publication series

NameEuropean Signal Processing Conference
ISSN (Electronic)2076-1465

Conference

Conference27th European Signal Processing Conference 2019
Abbreviated titleEUSIPCO
CountrySpain
CityA Coruna
Period2/09/197/09/19
Internet address

Keywords

  • Bayesian statistics
  • Detection
  • Inverse problems
  • Lidar
  • Low-photon imaging
  • Sensing

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Tachella, J., Altmann, Y., Tourneret, J-Y., & McLaughlin, S. (2019). Fast surface detection in single-photon Lidar waveforms. In 2019 27th European Signal Processing Conference (EUSIPCO) [8903062] (European Signal Processing Conference). IEEE. https://doi.org/10.23919/EUSIPCO.2019.8903062