Abstract
Original language | English |
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Publication status | Accepted/In press - 3 Jun 2019 |
Event | 27th European Signal Processing Conference 2019 - A Coruna, Spain, A Coruna, Spain Duration: 2 Sep 2019 → 7 Sep 2019 http://eusipco2019.org/ |
Conference
Conference | 27th European Signal Processing Conference 2019 |
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Abbreviated title | EUSIPCO |
Country | Spain |
City | A Coruna |
Period | 2/09/19 → 7/09/19 |
Internet address |
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Fast surface detection in single-photon Lidar waveforms. / Tachella, Julián; Altmann, Yoann; Tourneret, Jean-Yves; McLaughlin, Stephen.
2019. Paper presented at 27th European Signal Processing Conference 2019, A Coruna, Spain.Research output: Contribution to conference › Paper
TY - CONF
T1 - Fast surface detection in single-photon Lidar waveforms
AU - Tachella, Julián
AU - Altmann, Yoann
AU - Tourneret, Jean-Yves
AU - McLaughlin, Stephen
PY - 2019/6/3
Y1 - 2019/6/3
N2 - 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.
AB - 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.
M3 - Paper
ER -