Abstract
In this article, a new method for camera self-calibration is presented. A correspondent matrix can be built by matching the corresponding vanishing points between two images and the proposed method must use at least two of these matrices for calibration. The images are all taken from different orientations in any locations for the same object in space. The vanishing points in the image are the projective points of the infinity points in space. So in the calibration, it has no constraints about the location and the orientation of the camera and the calibration procedure is easy. Since when the internal parameters of camera are changed during the task, the camera can be easily and effectively calibrated if the vanishing points can be conveniently gotten from the task images or the camera can insert three or more images about the same object during the ongoing task. Compared with the traditional methods of camera self-calibration, this method is an easier and more effective calibration method and also it is an online calibration with accurate results.
Supported by NSFC project (grant no 60872099).
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Chang, D., Wang, K., Wang, L. (2011). Camera Self-calibration Based on the Vanishing Points. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23896-3_6
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DOI: https://doi.org/10.1007/978-3-642-23896-3_6
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