Single-Photon 3D Imaging with Equi-Depth Photon Histograms

• URL: http://arxiv.org/abs/2408.16150v1
• Date: Wed, 28 Aug 2024 22:02:38 GMT
• Title: Single-Photon 3D Imaging with Equi-Depth Photon Histograms
• Authors: Kaustubh Sadekar, David Maier, Atul Ingle,
• Abstract summary: Single-photon 3D cameras estimate the round-trip time of a laser pulse by forming equi-width (EW) histograms of detected photon timestamps. EW histograms require high bandwidth and in-pixel memory, making SPCs less attractive in resource-constrained settings. We propose a 3D sensing technique based on equi-depth (ED) histograms.
• Score: 4.432168053497992
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Single-photon cameras present a promising avenue for high-resolution 3D imaging. They have ultra-high sensitivity -- down to individual photons -- and can record photon arrival times with extremely high (sub-nanosecond) resolution. Single-photon 3D cameras estimate the round-trip time of a laser pulse by forming equi-width (EW) histograms of detected photon timestamps. Acquiring and transferring such EW histograms requires high bandwidth and in-pixel memory, making SPCs less attractive in resource-constrained settings such as mobile devices and AR/VR headsets. In this work we propose a 3D sensing technique based on equi-depth (ED) histograms. ED histograms compress timestamp data more efficiently than EW histograms, reducing the bandwidth requirement. Moreover, to reduce the in-pixel memory requirement, we propose a lightweight algorithm to estimate ED histograms in an online fashion without explicitly storing the photon timestamps. This algorithm is amenable to future in-pixel implementations. We propose algorithms that process ED histograms to perform 3D computer-vision tasks of estimating scene distance maps and performing visual odometry under challenging conditions such as high ambient light. Our work paves the way towards lower bandwidth and reduced in-pixel memory requirements for SPCs, making them attractive for resource-constrained 3D vision applications. Project page: $\href{https://www.computational.camera/pedh}{https://www.computational.camera/pedh}$

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