A General Means for Depth Data Error Estimation of Depth Sensors

DOI

10.2991/cnci-19.2019.57How to use a DOI?

Keywords

RGB-D sensors, Depth data, point clouds, RMS error.

Abstract

At present the depth error estimation of the RGB-D sensor is aimed at a specific depth camera, the disadvantages of these methods is that it is put forword for a specific sensor and cannot be applied to the other sensors.In order to solve this problem, this paper proposes a general method to estimate the root mean square (RMS) error of depth data provided by general three-dimensional sensors. The method is applicable to three-dimensional sensors based on structured light, time-of-flight, stereo vision and other technologies. Use a common checkerboard to detect corner points and get two point clouds, one is the real point cloud of the image corner, and the other is the estimated point cloud of the corner point given by the device. After registrating of the two point clouds, the RMS error is calculated. The RMS error is generalized as a function of the distance between the RGB-D sensor and the checkerboard .The accuracy and practicability of the proposed method are verified by comparing it with the existing advanced depth error estimation methods.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qian She
AU  - Hongyang Yu
PY  - 2019/05
DA  - 2019/05
TI  - A General Means for Depth Data Error Estimation of Depth Sensors
BT  - Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019)
PB  - Atlantis Press
SP  - 418
EP  - 425
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnci-19.2019.57
DO  - 10.2991/cnci-19.2019.57
ID  - She2019/05
ER  -