Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/149096
Title: Voxel structure-based mesh reconstruction from a 3D point cloud
Authors: Lv, Chenlei
Lin, Weisi 
Zhao, Baoquan
Keywords: Engineering::Computer science and engineering::Computing methodologies::Computer graphics
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2021
Source: Lv, C., Lin, W. & Zhao, B. (2021). Voxel structure-based mesh reconstruction from a 3D point cloud. IEEE Transactions On Multimedia. https://dx.doi.org/10.1109/TMM.2021.3073265
Project: MOE2016-T2-2-057(S) 
Journal: IEEE Transactions on Multimedia 
Abstract: Mesh reconstruction from a 3D point cloud is an important topic in the fields of computer graphic, computer vision, and multimedia analysis. In this paper, we propose a voxel structure-based mesh reconstruction framework. It provides the intrinsic metric to improve the accuracy of local region detection. Based on the detected local regions, an initial reconstructed mesh can be obtained. With the mesh optimization in our framework, the initial reconstructed mesh is optimized into an isotropic one with the important geometric features such as external and internal edges. The experimental results indicate that our framework shows great advantages over peer ones in terms of mesh quality, geometric feature keeping, and processing speed.
URI: https://hdl.handle.net/10356/149096
ISSN: 1520-9210
DOI: 10.1109/TMM.2021.3073265
Schools: School of Computer Science and Engineering 
Rights: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TMM.2021.3073265.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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