Transientangelo: Few-Viewpoint Surface Reconstruction Using Single-Photon Lidar

We consider the problem of few-viewpoint 3D surface reconstruction using raw measurements from a lidar system. Lidar captures 3D scene geometry by emitting pulses of light to a target and recording the speed-of-light time delay of the reflected light. However, conventional lidar systems do not outpu...

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Bibliographic Details
Published inarXiv.org
Main Authors Luo, Weihan, Malik, Anagh, Lindell, David B
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 23.08.2024
Subjects
Backscattering
Image reconstruction
Lidar
Light
Photons
Regularization
Three dimensional models
Time lag
Time measurement
Waveforms
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Summary:We consider the problem of few-viewpoint 3D surface reconstruction using raw measurements from a lidar system. Lidar captures 3D scene geometry by emitting pulses of light to a target and recording the speed-of-light time delay of the reflected light. However, conventional lidar systems do not output the raw, captured waveforms of backscattered light; instead, they pre-process these data into a 3D point cloud. Since this procedure typically does not accurately model the noise statistics of the system, exploit spatial priors, or incorporate information about downstream tasks, it ultimately discards useful information that is encoded in raw measurements of backscattered light. Here, we propose to leverage raw measurements captured with a single-photon lidar system from multiple viewpoints to optimize a neural surface representation of a scene. The measurements consist of time-resolved photon count histograms, or transients, which capture information about backscattered light at picosecond time scales. Additionally, we develop new regularization strategies that improve robustness to photon noise, enabling accurate surface reconstruction with as few as 10 photons per pixel. Our method outperforms other techniques for few-viewpoint 3D reconstruction based on depth maps, point clouds, or conventional lidar as demonstrated in simulation and with captured data.
ISSN:2331-8422