Real-Time 3D Color Imaging with Single-Photon Lidar Data

J. Tachella, Y. Altmann, S. McLaughlin, J.-Y. Tourneret

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

2 Citations (Scopus)

Abstract

Single-photon lidar devices can acquire 3D data at very long range with high precision. Moreover, recent advances in lidar arrays have enabled acquisitions at very high frame rates. However, these devices place a severe bottleneck on the reconstruction algorithms, which have to handle very large volumes of noisy data. Recently, real-time 3D reconstruction of distributed surfaces has been demonstrated obtaining information at one wavelength. Here, we propose a new algorithm that achieves color 3D reconstruction without increasing the execution time nor the acquisition process of the realtime single-wavelength reconstruction system. The algorithm uses a coded aperture that compresses the data by considering a subset of the wavelengths per pixel. The reconstruction algorithm is based on a plug-and-play denoising framework, which benefits from off-the-shelf point cloud and image de-noisers. Experiments using real lidar data show the competitivity of the proposed method.

Original languageEnglish
Title of host publication2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
PublisherIEEE
Pages206-210
Number of pages5
ISBN (Electronic)9781728155494
DOIs
Publication statusPublished - 5 Mar 2020
Event8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing 2019 - Le Gosier, Le Gosier, Guadeloupe
Duration: 15 Dec 201918 Dec 2019
https://camsap19.ig.umons.ac.be/

Conference

Conference8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing 2019
Abbreviated titleCAMSAP 2019
Country/TerritoryGuadeloupe
CityLe Gosier
Period15/12/1918/12/19
Internet address

Keywords

  • Bayesian statistics
  • detection
  • inverse problems
  • lidar
  • low-photon imaging and sensing

ASJC Scopus subject areas

  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

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