Binocular vision measurement and its application in full-field convex deformation of concrete-filled steel tubular columns
By Yunchao Tang, Lijuan Li, W. Feng, Feng Liu, Xiangjun Zou, Minyong Chen. Measurement, 2018
62 citations recorded by the source corpus.
Abstract This paper presents a non-contact 3D deformation measurement method based on binocular vision. The proposed method was tested in the determination of the deformation and strain of concrete-filled steel tubes. Based on the proposed image-processing algorithm and the principle of 3D deformation measurement, the least-square-based circle-fitting algorithm was presented in this article and was applied to binocular vision systems for the static and dynamic collection of full-field 3D deformation data in concrete-filled steel tubular columns. Three-dimensional reconstruction was performed, and the results obtained were compared with those of a contact measuring tool. The test results showed that the mean relative errors of the maximum convex diameter in the visual static and dynamic measurements were 0.19% and 0.33%, respectively, and the mean relative error in the full-field strain in the visual measurement was between 0.20% and 0.49%, which shows that the proposed visual method comprehensively reflects the deformation process and full-field strain values of the components under engineering ISO Tolerance (IT7) accuracy requirements. This method can be used as a reasonable alternative to traditional contact measuring methods.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/7390ded8bc47485b64f96bf8118fb5bba34ef4df
Citations in the corpus
- Recognition and Localization Methods for Vision-Based Fruit Picking Robots: A Review (2020, unknown): “Tang et al. (2018) use binocular vision to track vibrations caused by terrain deformation and to detect the 3D deformation surface.”