학술논문

A Fusion Algorithm of Relative Orientation for Close Range Industrial Photogrammetry
Document Type
Conference
Author
Source
2024 IEEE 4th International Conference on Power, Electronics and Computer Applications (ICPECA) Power, Electronics and Computer Applications (ICPECA), 2024 IEEE 4th International Conference on. :1170-1174 Jan, 2024
Subject
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Photography
Industries
Computer applications
Cost function
Cameras
Vectors
Power electronics
fusion algorithm of relative orientation
digital close range industrial photogrammetry
essential matrix
non-linear optimization
Language
Abstract
In order to satisfy the multiple-baselines and large-dip-angles close range photogrammetry applied in industry, a fusion algorithm of relative orientation is presented. In this algorithm, the initial values of the relative orientation parameters are established by the decomposition of the essential matrix, and then the precise solution of the parameters are calculated by a nonlinear optimization. First, the relationship between the essential matrix and the orientation parameters is derived by the determinant from the coplanarity condition, and then the rotation matrix and translation vector between two images are calculated by singular value decomposition (SVD) of the essential matrix, including the removal of the pseudo solutions. Second, according to the coplanarity condition equation, the cost function of relative orientation parameters for non-linear optimization is build. Finally, the result in comparison experiment indicates that the fusion algorithm has acquired better stabilization and high precision.