Geometry-Based Camera Calibration Using Five-Point Correspondences From a Single Image
| Autor: | Hua-Tsung Chen |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Orientation (computer vision)
Computer science Calibration (statistics) business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Astrophysics::Instrumentation and Methods for Astrophysics 020207 software engineering Bundle adjustment 02 engineering and technology Real image Camera auto-calibration Computer Science::Computer Vision and Pattern Recognition 0202 electrical engineering electronic engineering information engineering Media Technology Image noise Focal length 020201 artificial intelligence & image processing Computer vision Artificial intelligence Electrical and Electronic Engineering business Camera resectioning |
| Zdroj: | IEEE Transactions on Circuits and Systems for Video Technology. 27:2555-2566 |
| ISSN: | 1558-2205 1051-8215 |
| DOI: | 10.1109/tcsvt.2016.2595319 |
| Popis: | As an essential step in many computer vision tasks, camera calibration has been studied extensively. In this paper, we propose a novel calibration technique that, based on geometric analysis, camera parameters can be estimated effectively and accurately from just one view of only five corresponding points. Our core contribution is the geometric analysis for deriving the basic equations to realize camera calibration from four coplanar corresponding points and a fifth noncoplanar one. The position, orientation, and focal length of a zooming camera can be directly estimated with unique solution. The estimated parameters are further optimized by the bundle adjustment technique. The proposed calibration method is examined and evaluated on both computer simulated data and real images. The experimental results confirm the validity of the proposed method that camera parameters can be estimated with sufficient accuracy using just five-point correspondences from a single image, even in the presence of image noise. |
| Databáze: | OpenAIRE |
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