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Cited 3 time in webofscience Cited 5 time in scopus
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Real-time 3D reconstruction method using massive multi-sensor data analysis and fusion

Authors
Cho, SeoungjaeCho, Kyungeun
Issue Date
Jun-2019
Publisher
SPRINGER
Keywords
Unmanned ground vehicle; 3D reconstruction; 3D point cloud; Object segmentation; Template mesh
Citation
JOURNAL OF SUPERCOMPUTING, v.75, no.6, pp 3229 - 3248
Pages
20
Indexed
SCI
SCIE
SCOPUS
Journal Title
JOURNAL OF SUPERCOMPUTING
Volume
75
Number
6
Start Page
3229
End Page
3248
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/8073
DOI
10.1007/s11227-019-02747-3
ISSN
0920-8542
1573-0484
Abstract
This paper proposes a method to reconstruct three-dimensional (3D) objects using real-time fusion and analysis of multiple sensor data. This paper attempts to create a realistic 3D visualization with which a remote pilot can intuitively control a remote unmanned robot by utilizing the characteristics of massive sensor data. The 3D reconstruction system proposed in this paper is comprised of 3D and two-dimensional (2D) data segmentation method, a 3D reconstruction method applied to each object, and a projective texture mapping method. Specifically, we propose applying both a 2D region extraction method and a 3D mesh modeling method to each object. The proposed schemes are implemented as a real-time application to verify real-time performance. This paper proves that 3D meshes can be modeled in real time by using the proposed method. The proposed method allows the remote control of a robot for real-time 3D rendering of remote scenes, which is essential for various tasks in areas that cannot be easily accessed by humans.
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College of Advanced Convergence Engineering (Department of Computer Science and Artificial Intelligence)
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