Cubic Range Error Model for Stereo Vision with Illuminators
Marius Huber, Timo Hinzmann, Roland Siegwart, and Larry H. Matthies

TL;DR
This paper introduces a cubic range error model for stereo vision systems with illuminators, validated experimentally, which improves uncertainty estimation for low-light depth sensing applications.
Contribution
The paper proposes and validates a novel cubic range error model specifically for stereo systems with integrated illuminators, simplifying sensor uncertainty quantification.
Findings
Range error is approximately cubic in range.
Experimental validation shows the exponent is between 2.4 and 2.6.
Model considers shot noise as the primary source of error.
Abstract
Use of low-cost depth sensors, such as a stereo camera setup with illuminators, is of particular interest for numerous applications ranging from robotics and transportation to mixed and augmented reality. The ability to quantify noise is crucial for these applications, e.g., when the sensor is used for map generation or to develop a sensor scheduling policy in a multi-sensor setup. Range error models provide uncertainty estimates and help weigh the data correctly in instances where range measurements are taken from different vantage points or with different sensors. The weighing is important to fuse range data into a map in a meaningful way, i.e., the high confidence data is relied on most heavily. Such a model is derived in this work. We show that the range error for stereo systems with integrated illuminators is cubic and validate the proposed model experimentally with an…
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