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Sensors 2017, 17(1), 92; doi:10.3390/s17010092

Depth Errors Analysis and Correction for Time-of-Flight (ToF) Cameras

1,* , 1,2
,
2
,
2
and
3
1
Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China
2
Department of Automation, Tsinghua University, Beijing 100084, China
3
Shenzhen Graduate School, Tsinghua University, Shenzhen 518055, China
*
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 2 September 2016 / Revised: 7 December 2016 / Accepted: 9 December 2016 / Published: 5 January 2017
(This article belongs to the Special Issue Imaging: Sensors and Technologies)
View Full-Text   |   Download PDF [5045 KB, uploaded 6 January 2017]   |  

Abstract

Time-of-Flight (ToF) cameras, a technology which has developed rapidly in recent years, are 3D imaging sensors providing a depth image as well as an amplitude image with a high frame rate. As a ToF camera is limited by the imaging conditions and external environment, its captured data are always subject to certain errors. This paper analyzes the influence of typical external distractions including material, color, distance, lighting, etc. on the depth error of ToF cameras. Our experiments indicated that factors such as lighting, color, material, and distance could cause different influences on the depth error of ToF cameras. However, since the forms of errors are uncertain, it’s difficult to summarize them in a unified law. To further improve the measurement accuracy, this paper proposes an error correction method based on Particle Filter-Support Vector Machine (PF-SVM). Moreover, the experiment results showed that this method can effectively reduce the depth error of ToF cameras to 4.6 mm within its full measurement range (0.5–5 m). View Full-Text
Keywords: ToF camera; depth error; error modeling; error correction; particle filter; SVM ToF camera; depth error; error modeling; error correction; particle filter; SVM
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He, Y.; Liang, B.; Zou, Y.; He, J.; Yang, J. Depth Errors Analysis and Correction for Time-of-Flight (ToF) Cameras. Sensors 2017, 17, 92.

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