# Unlocking the Performance of Proximity Sensors by Utilizing Transient Histograms

arXiv: https://arxiv.org/abs/2308.13473 · HTML: https://mlsanity.com/paper/2308.13473/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 35 references that are in the map.
- First posted on arXiv 25 Aug 2023.

## Builds on (most cited first, 9 of 9)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Non-line-of-Sight Imaging via Neural Transient Fields](https://mlsanity.com/paper/2101.00373/) (2021)
- [Asynchronous Single-Photon 3D Imaging](https://mlsanity.com/paper/1908.06372/) (2019)
- [Photon-Flooded Single-Photon 3D Cameras](https://mlsanity.com/paper/1903.08347/) (2019)
- [Physics to the Rescue: Deep Non-line-of-sight Reconstruction for High-speed Imaging](https://mlsanity.com/paper/2205.01679/) (2022)
- [3D Scene Inference from Transient Histograms](https://mlsanity.com/paper/2211.05094/) (2022)
- [Contact Anticipation for Physical Human-Robot Interaction with Robotic Manipulators using Onboard Proximity Sensors](https://mlsanity.com/paper/2110.11516/) (2021)
- [Real-time, low-cost multi-person 3D pose estimation](https://mlsanity.com/paper/2110.11414/) (2021)
- [Large-scale single-photon imaging](https://mlsanity.com/paper/2212.13654/) (2022)

## Built on by (most cited first, 4 of 4)

- [Towards 3D Vision with Low-Cost Single-Photon Cameras](https://mlsanity.com/paper/2403.17801/) (2024)
- [Blurred LiDAR for Sharper 3D: Robust Handheld 3D Scanning with Diffuse LiDAR and RGB](https://mlsanity.com/paper/2411.19474/) (2024)
- [Using a Distance Sensor to Detect Deviations in a Planar Surface](https://mlsanity.com/paper/2408.03838/) (2024)
- [Recovering Parametric Scenes from Very Few Time-of-Flight Pixels](https://mlsanity.com/paper/2509.16132/) (2025)

## Abstract (arXiv)

We provide methods which recover planar scene geometry by utilizing the transient histograms captured by a class of close-range time-of-flight (ToF) distance sensor. A transient histogram is a one dimensional temporal waveform which encodes the arrival time of photons incident on the ToF sensor. Typically, a sensor processes the transient histogram using a proprietary algorithm to produce distance estimates, which are commonly used in several robotics applications. Our methods utilize the transient histogram directly to enable recovery of planar geometry more accurately than is possible using only proprietary distance estimates, and consistent recovery of the albedo of the planar surface, which is not possible with proprietary distance estimates alone. This is accomplished via a differentiable rendering pipeline, which simulates the transient imaging process, allowing direct optimization of scene geometry to match observations. To validate our methods, we capture 3,800 measurements of eight planar surfaces from a wide range of viewpoints, and show that our method outperforms the proprietary-distance-estimate baseline by an order of magnitude in most scenarios. We demonstrate a simple robotics application which uses our method to sense the distance to and slope of a planar surface from a sensor mounted on the end effector of a robot arm.