3D Correspondence and Point Projection Method for Structures Deformation Analysis

IEEE Access

Juliano E. N. Masson¹  Aurelio G. Melo²  Leonardo M. Honorio²  Felipe M. Dias²  Milena F. Pinto³ 

[1] Department of Automation and Systems, Federal University of Santa Catarina, Florian&x00F3;Department of Electrical Engineering, Federal University of Juiz de Fora, Juiz de Fora, Brazil;Department of Electronics Engineering, Federal Center for Technological Education of Rio de Janeiro, Rio de Janeiro, Brazil;

关键词: Aerial inspection;    point cloud change detection;    structural analysis;    structure from motion;    3D reconstruction;   

DOI  :  10.1109/ACCESS.2020.3027205

来源: DOAJ

【 摘 要 】

Mining slopes, electrical power generation dams and several big construction enterprises demands continuous inspections. The size and diversity of these structures demands high precision and portable approach. In such environments, 3D reconstruction methodologies are able to capture and analyze the real world in detail. However, the accuracy and precision can affect the ability to process and interpret the acquired data. For instance, laser scanning is a very accurate method and can deliver a higher quality result. Meanwhile, 3D photogrammetry using a single camera and Structure From Motion (SFM) have their performance correlated with the image quality. In a typical application, 3D data from reconstruction is pre-processed by a specialist. Then, it is stored for comparison and analyzed over time. The posterior analysis has several challenges associated with the reconstruction process characteristics. Several techniques have been developed to allow the comparison of point cloud captured at different epochs. Therefore, this research work presents a new methodology to perform alignment and comparison of point clouds, namely 3D-CP2, an acronym for 3D Correspondence and Point Projection. This method intends to analyze the point cloud motion to be applied in terrestrial 3D SFM reconstructions. Besides, the technique can also be used in many other related applications. The methodology developed in this work is applied in controlled experiments and real use cases to show its potential for point cloud displacements analysis. The results showed that the proposed method is efficient and can produce results more accurately than the referenced literature.

【 授权许可】

Unknown