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Sensors 2018, 18(9), 3122;

A Versatile Method for Depth Data Error Estimation in RGB-D Sensors

Natalnet Associate Laboratories, Federal University of Rio Grande do Norte, Campus Universitário, Natal RN 59.078-970, Brazil
Institute of Computing, Fluminense Federal University, Campus Praia Vermelha, Niteroi RJ 24.310-346, Brazil
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Received: 8 August 2018 / Revised: 10 September 2018 / Accepted: 13 September 2018 / Published: 16 September 2018
(This article belongs to the Special Issue Depth Sensors and 3D Vision)
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We propose a versatile method for estimating the RMS error of depth data provided by generic 3D sensors with the capability of generating RGB and depth (D) data of the scene, i.e., the ones based on techniques such as structured light, time of flight and stereo. A common checkerboard is used, the corners are detected and two point clouds are created, one with the real coordinates of the pattern corners and one with the corner coordinates given by the device. After a registration of these two clouds, the RMS error is computed. Then, using curve fittings methods, an equation is obtained that generalizes the RMS error as a function of the distance between the sensor and the checkerboard pattern. The depth errors estimated by our method are compared to those estimated by state-of-the-art approaches, validating its accuracy and utility. This method can be used to rapidly estimate the quality of RGB-D sensors, facilitating robotics applications as SLAM and object recognition. View Full-Text
Keywords: RGB-D sensors; accuracy; RMS error RGB-D sensors; accuracy; RMS error

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Cabrera, E.V.; Ortiz, L.E.; Silva, B.M.F.; Clua, E.W.G.; Gonçalves, L.M.G. A Versatile Method for Depth Data Error Estimation in RGB-D Sensors. Sensors 2018, 18, 3122.

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