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- Title
基于众源影像的三维重建方法.
- Authors
王志明; 刘丹
- Abstract
At present, It is difficult to filter the data from crowd-sourced images, which leads to the geometric missing and noises in the point cloud data generated from the images. To solve this problem, a method of 3D reconstruction based on crowd-sourced images was presented. Firstly, the methods based on website application programming interface (API) and web page analysis were used to obtain the crowd-sourced images. Then, the crowd-sourced images were filtered by deep learning to obtain high-quality crowd-sourced pictures data. Finally, the structure from motion (SFM) algorithm was used to complete the 3D reconstruction based on the filtered crowd-sourced images. It is concluded that image set screened by deep learning algorithm is more suitable for 3D reconstruction, so as to solve the disadvantages and deficiencies of crowd-sourced image, an emerging data source, in the application of 3D modeling.
- Publication
Science Technology & Engineering, 2022, Vol 22, Issue 12, p4729
- ISSN
1671-1815
- Publication type
Article