In:
Photogrammetric Engineering & Remote Sensing, American Society for Photogrammetry and Remote Sensing, Vol. 86, No. 11 ( 2020-11-01), p. 677-694
Abstract:
To address the high-cost problem of the current three-dimensional ( 〈 small 〉 3D 〈 /small 〉 ) reconstruction for urban buildings, a new technical framework is proposed to generate 〈 small 〉 3D 〈 /small 〉 building facade information using crowd-sourced photos and two-dimensional
(2D) building vector data in this paper. The crowd-sourced photos mainly consisted of Tencent street view images and other-source photos, which were collected from three platforms, including search engines, social media, and mobile phones. The photos were selected and grouped first, and then a structure from motion algorithm was used for 〈 small 〉 3D 〈 /small 〉 reconstruction. Finally, the reconstructed point clouds were registered with 2D building vector data. The test implementation was conducted in the Jianye District of Nanjing, China, and the generated point clouds
showed a good fit with the true values. The proposed 〈 small 〉 3D 〈 /small 〉 reconstruction method represents a multi-sourced data integration process. The advantage of the proposed approach lies in the open source and low-cost data used in this study.
Type of Medium:
Online Resource
ISSN:
0099-1112
DOI:
10.14358/PERS.86.11.677
Language:
English
Publisher:
American Society for Photogrammetry and Remote Sensing
Publication Date:
2020
detail.hit.zdb_id:
2317128-5
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