Journal of Geodesy and Geoinformation Science ›› 2022, Vol. 5 ›› Issue (4): 23-37.doi: 10.11947/j.JGGS.2022.0403

• Special Issue • Previous Articles     Next Articles

A Skeletal Camera Network for Close-range Images with a Data Driven Approach in Analyzing Stereo Configuration

Zhihua XU1,2(),Lingling QU1   

  1. 1. College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
    2. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
  • Received:2022-06-15 Accepted:2022-09-15 Online:2022-12-20 Published:2023-03-15
  • About author:Zhihua XU, E-mail:
  • Supported by:
    National Natural Science Foundation of China(41701534);Open Fund of State Key Laboratory of Coal Resources and Safe Mining(SKLCRSM19KFA01);Ecological and Smart Mine Joint Foundation of Hebei Province(E2020402086);State Key Laboratory ofGeohazard Prevention and Geoenvironment Protection(SKLGP2019K015)


Structure-from-Motion (SfM) techniques have been widely used for 3D geometry reconstruction from multi-view images. Nevertheless, the efficiency and quality of the reconstructed geometry depends on multiple factors, i.e., the base-height ratio, intersection angle, overlap, and ground control points, etc., which are rarely quantified in real-world applications. To answer this question, in this paper, we take a data-driven approach by analyzing hundreds of terrestrial stereo image configurations through a typical SfM algorithm. Two main meta-parameters with respect to base-height ratio and intersection angle are analyzed. Following the results, we propose a Skeletal Camera Network (SCN) and embed it into the SfM to lead to a novel SfM scheme called SCN-SfM, which limits tie-point matching to the remaining connected image pairs in SCN. The proposed method was applied in three terrestrial datasets. Experimental results have demonstrated the effectiveness of the proposed SCN-SfM to achieve 3D geometry with higher accuracy and fast time efficiency compared to the typical SfM method, whereas the completeness of the geometry is comparable.

Key words: 3D geometry reconstruction; geometric factors; skeletal camera network; Structure-from-Motion; tie-point matching; terrestrial stereo images