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A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light
Depth information has been used in many fields because of its low cost and easy availability, since the Microsoft Kinect was released. However, the Kinect and Kinect-like RGB-D sensors show limited performance in certain applications and place high demands on accuracy and robustness of depth informa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422166/ https://www.ncbi.nlm.nih.gov/pubmed/28397759 http://dx.doi.org/10.3390/s17040805 |
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author | Yao, Huimin Ge, Chenyang Xue, Jianru Zheng, Nanning |
author_facet | Yao, Huimin Ge, Chenyang Xue, Jianru Zheng, Nanning |
author_sort | Yao, Huimin |
collection | PubMed |
description | Depth information has been used in many fields because of its low cost and easy availability, since the Microsoft Kinect was released. However, the Kinect and Kinect-like RGB-D sensors show limited performance in certain applications and place high demands on accuracy and robustness of depth information. In this paper, we propose a depth sensing system that contains a laser projector similar to that used in the Kinect, and two infrared cameras located on both sides of the laser projector, to obtain higher spatial resolution depth information. We apply the block-matching algorithm to estimate the disparity. To improve the spatial resolution, we reduce the size of matching blocks, but smaller matching blocks generate lower matching precision. To address this problem, we combine two matching modes (binocular mode and monocular mode) in the disparity estimation process. Experimental results show that our method can obtain higher spatial resolution depth without loss of the quality of the range image, compared with the Kinect. Furthermore, our algorithm is implemented on a low-cost hardware platform, and the system can support the resolution of 1280 × 960, and up to a speed of 60 frames per second, for depth image sequences. |
format | Online Article Text |
id | pubmed-5422166 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54221662017-05-12 A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light Yao, Huimin Ge, Chenyang Xue, Jianru Zheng, Nanning Sensors (Basel) Article Depth information has been used in many fields because of its low cost and easy availability, since the Microsoft Kinect was released. However, the Kinect and Kinect-like RGB-D sensors show limited performance in certain applications and place high demands on accuracy and robustness of depth information. In this paper, we propose a depth sensing system that contains a laser projector similar to that used in the Kinect, and two infrared cameras located on both sides of the laser projector, to obtain higher spatial resolution depth information. We apply the block-matching algorithm to estimate the disparity. To improve the spatial resolution, we reduce the size of matching blocks, but smaller matching blocks generate lower matching precision. To address this problem, we combine two matching modes (binocular mode and monocular mode) in the disparity estimation process. Experimental results show that our method can obtain higher spatial resolution depth without loss of the quality of the range image, compared with the Kinect. Furthermore, our algorithm is implemented on a low-cost hardware platform, and the system can support the resolution of 1280 × 960, and up to a speed of 60 frames per second, for depth image sequences. MDPI 2017-04-08 /pmc/articles/PMC5422166/ /pubmed/28397759 http://dx.doi.org/10.3390/s17040805 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yao, Huimin Ge, Chenyang Xue, Jianru Zheng, Nanning A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light |
title | A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light |
title_full | A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light |
title_fullStr | A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light |
title_full_unstemmed | A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light |
title_short | A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light |
title_sort | high spatial resolution depth sensing method based on binocular structured light |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422166/ https://www.ncbi.nlm.nih.gov/pubmed/28397759 http://dx.doi.org/10.3390/s17040805 |
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