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Camera self-calibration method based on two vanishing points
- Source :
- SPIE Proceedings.
- Publication Year :
- 2015
- Publisher :
- SPIE, 2015.
-
Abstract
- Camera calibration is one of the indispensable processes to obtain 3D depth information from 2D images in the field of computer vision. Camera self-calibration is more convenient and flexible, especially in the application of large depth of fields, wide fields of view, and scene conversion, as well as other occasions like zooms. In this paper, a self-calibration method based on two vanishing points is proposed, the geometric characteristic of disappear points formed by two groups of orthogonal parallel lines is applied to camera self-calibration. By using the vectors’ orthogonal properties of connection optical centers and the vanishing points, the constraint equations on the camera intrinsic parameters are established. By this method, four internal parameters of the camera can be solved though only four images taken from different viewpoints in a scene. Compared with the two other self-calibration methods with absolute quadric and calibration plate, the method based on two vanishing points does not require calibration objects, camera movement, the information on the size and location of parallel lines, without strict experimental equipment, and having convenient calibration process and simple algorithm. Compared with the experimental results of the method based on calibration plate, self-calibration method by using machine vision software Halcon, the practicability and effectiveness of the proposed method in this paper is verified.
- Subjects :
- Quadric
business.industry
Calibration (statistics)
Machine vision
Camera matrix
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Astrophysics::Instrumentation and Methods for Astrophysics
Parallel
Camera auto-calibration
Computer Science::Computer Vision and Pattern Recognition
Computer vision
Artificial intelligence
Vanishing point
business
Mathematics
Camera resectioning
Subjects
Details
- ISSN :
- 0277786X
- Database :
- OpenAIRE
- Journal :
- SPIE Proceedings
- Accession number :
- edsair.doi...........ebe7035b74cecbdf757855588c3371e2
- Full Text :
- https://doi.org/10.1117/12.2202761