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Article

Detail Preserved Surface Reconstruction from Point Cloud

by 1,2, 1,2,* and 1,2
1
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(6), 1278; https://doi.org/10.3390/s19061278
Received: 18 February 2019 / Revised: 9 March 2019 / Accepted: 11 March 2019 / Published: 13 March 2019
(This article belongs to the Special Issue Sensor Signal and Information Processing II)
In this paper, we put forward a new method for surface reconstruction from image-based point clouds. In particular, we introduce a new visibility model for each line of sight to preserve scene details without decreasing the noise filtering ability. To make the proposed method suitable for point clouds with heavy noise, we introduce a new likelihood energy term to the total energy of the binary labeling problem of Delaunay tetrahedra, and we give its s-t graph implementation. Besides, we further improve the performance of the proposed method with the dense visibility technique, which helps to keep the object edge sharp. The experimental result shows that the proposed method rivalled the state-of-the-art methods in terms of accuracy and completeness, and performed better with reference to detail preservation. View Full-Text
Keywords: computer vision; 3D reconstruction; point cloud computer vision; 3D reconstruction; point cloud
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MDPI and ACS Style

Zhou, Y.; Shen, S.; Hu, Z. Detail Preserved Surface Reconstruction from Point Cloud. Sensors 2019, 19, 1278. https://doi.org/10.3390/s19061278

AMA Style

Zhou Y, Shen S, Hu Z. Detail Preserved Surface Reconstruction from Point Cloud. Sensors. 2019; 19(6):1278. https://doi.org/10.3390/s19061278

Chicago/Turabian Style

Zhou, Yang, Shuhan Shen, and Zhanyi Hu. 2019. "Detail Preserved Surface Reconstruction from Point Cloud" Sensors 19, no. 6: 1278. https://doi.org/10.3390/s19061278

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