Journal
ETRI JOURNAL
Volume 40, Issue 6, Pages 788-793Publisher
WILEY
DOI: 10.4218/etrij.2017-0298
Keywords
3D reconstruction; clustering; feature extraction; PMVS; UAV
Funding
- Natural Science Foundation of Shaanxi Province, China [2017JQ6048]
- Fundamental Research Funds for the Central Universities, China [310824161009]
- Postdoctoral Science Foundation of China [2015M582589]
- Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin University of Electronic Technology, China [DH201711]
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3D reconstruction of urban architecture, land, and roads is an important part of building a digital city. Unmanned aerial vehicles (UAVs) are gradually replacing other platforms, such as satellites and aircraft, in geographical image collection; the reason for this is not only lower cost and higher efficiency, but also higher data accuracy and a larger amount of obtained information. Recent 3D reconstruction algorithms have a high degree of automation, but their computation time is long and the reconstruction models may have many voids. This paper decomposes the object into multiple regional parallel reconstructions using the clustering principle, to reduce the computation time and improve the model quality. It is proposed to detect the planar area under low resolution, and then reduce the number of point clouds in the complex area.
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