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

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.

Cite

Text

Sadekar et al. "Single-Photon 3D Imaging with Equi-Depth Photon Histograms." Proceedings of the European Conference on Computer Vision (ECCV), 2024. doi:10.1007/978-3-031-73039-9_22

Markdown

[Sadekar et al. "Single-Photon 3D Imaging with Equi-Depth Photon Histograms." Proceedings of the European Conference on Computer Vision (ECCV), 2024.](https://mlanthology.org/eccv/2024/sadekar2024eccv-singlephoton/) doi:10.1007/978-3-031-73039-9_22

BibTeX

@inproceedings{sadekar2024eccv-singlephoton,
  title     = {{Single-Photon 3D Imaging with Equi-Depth Photon Histograms}},
  author    = {Sadekar, Kaustubh and Maier, David and Ingle, Atul},
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
  year      = {2024},
  doi       = {10.1007/978-3-031-73039-9_22},
  url       = {https://mlanthology.org/eccv/2024/sadekar2024eccv-singlephoton/}
}