Building Facade Reconstruction Using Crowd- Sourced Photos and Two-Dimensional Maps

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.