Unlocking the Performance of Proximity Sensors by Utilizing Transient Histograms
Carter Sifferman, Yeping Wang, Mohit Gupta, and Michael Gleicher

TL;DR
This paper introduces a novel approach that directly utilizes transient histograms from ToF sensors to improve planar scene geometry recovery and albedo estimation, outperforming traditional proprietary algorithms.
Contribution
The authors develop a differentiable rendering pipeline that directly optimizes scene geometry from transient histograms, enhancing accuracy over proprietary distance estimates.
Findings
Outperforms proprietary algorithms by an order of magnitude in accuracy.
Enables simultaneous recovery of geometry and surface albedo.
Validates method with 3,800 measurements across diverse viewpoints.
Abstract
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…
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Taxonomy
TopicsAdvanced Optical Sensing Technologies · Target Tracking and Data Fusion in Sensor Networks · Analytical Chemistry and Sensors
