4.7 Article

Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas

Journal

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
Volume 139, Issue -, Pages 119-132

Publisher

ELSEVIER
DOI: 10.1016/j.isprsjprs.2018.03.004

Keywords

Aerial oblique imagery; Terrestrial imagery; Photogrammetry; 3D modeling

Funding

  1. Research Grants Council of Hong Kong [PolyU 152211/18E]
  2. Hong Kong Polytechnic University [1-ZE24, 4-BCCQ]

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Photorealistic three-dimensional (3D) models are fundamental to the spatial data infrastructure of a digital city, and have numerous potential applications in areas such as urban planning, urban management, urban monitoring, and urban environmental studies. Recent developments in aerial oblique photogrammetry based on aircraft or unmanned aerial vehicles (UAVs) offer promising techniques for 3D modeling. However, 3D models generated from aerial oblique imagery in urban areas with densely distributed highrise buildings may show geometric defects and blurred textures, especially on building facades, due to problems such as occlusion and large camera tilt angles. Meanwhile, mobile mapping systems (MMSs) can capture terrestrial images of close-range objects from a complementary view on the ground at a high level of detail, but do not offer full coverage. The integration of aerial oblique imagery with terrestrial imagery offers promising opportunities to optimize 3D modeling in urban areas. This paper presents a novel method of integrating these two image types through automatic feature matching and combined bundle adjustment between them, and based on the integrated results to optimize the geometry and texture of the 3D models generated from aerial oblique imagery. Experimental analyses were conducted on two datasets of aerial and terrestrial images collected in Dortmund, Germany and in Hong Kong. The results indicate that the proposed approach effectively integrates images from the two platforms and thereby improves 3D modeling in urban areas. (C) 2018 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

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