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An approach of point cloud denoising based on improved bilateral filtering
Author(s): Zeling Zheng; Songmin Jia; Guoliang Zhang; Xiuzhi Li; Xiangyin Zhang
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Paper Abstract

An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.

Paper Details

Date Published: 10 April 2018
PDF: 7 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061557 (10 April 2018); doi: 10.1117/12.2303607
Show Author Affiliations
Zeling Zheng, Beijing Univ. of Technology (China)
Beijing Key Lab. of Computational Intelligence and Intelligent System (China)
Songmin Jia, Beijing Univ. of Technology (China)
Beijing Key Lab. of Computational Intelligence and Intelligent System (China)
Guoliang Zhang, Beijing Univ. of Technology (China)
Beijing Key Lab. of Computational Intelligence and Intelligent System (China)
Xiuzhi Li, Beijing Univ. of Technology (China)
Beijing Key Lab. of Computational Intelligence and Intelligent System (China)
Xiangyin Zhang, Beijing Univ. of Technology (China)
Beijing Key Lab. of Computational Intelligence and Intelligent System (China)


Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

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