The common self-polar triangle of concentric circles and its application to camera calibration

Author(s):  
Haifei Huang ◽  
Hui Zhang ◽  
Yiu-ming Cheung
2013 ◽  
Vol 54 ◽  
pp. 185-190 ◽  
Author(s):  
Xinyu Chen ◽  
Ying Hu ◽  
Zi Ma ◽  
Shuanghe Yu ◽  
Yuqing Chen

Author(s):  
Shubham Rohan Asthana

In several machine vision applications, a fundamental step is to precisely determine the relation between the image of the object and its physical dimension by performing a calibration process. The aim is to devise an enhanced mechanism for camera calibration in order to improve the already existing methods in OpenCV. A good calibration is important when we need to reconstruct a world model or interact with the world as in case of robot, hand-eye coordination. In order to meet the rising demands for higher accuracy various calibration techniques have been developed but they are unable in obtaining precise results. In this paper we propose an enhanced camera calibration procedure using a special grid pattern of concentric circles with special markers. The overall objective is to minimize the re-projection for good camera calibration.


Author(s):  
Qi Zhang ◽  
Qing Wang

Due to the trade-off between spatial resolution and angular resolution of the light field, it is difficult to extract high precision corner points and line features from light fields for calibration. A novel calibration pattern of separate circles is designed, and a light field camera calibration method based on common self-polar triangle with respect to separate circles is proposed in this paper. First, we explore the uniquity and reconstruction of common self-polar triangle with respect to sperate circles. Then, based on projections of the multi-projection-center model on the plane and conic, the common self-polar triangle on the sub-aperture image is reconstructed and used to estimate planar homography. Finally, a light field camera calibration algorithm is then proposed, including linear initialization and non-linear optimization. Experimental results on both synthetic and real data have verified the effectiveness and robustness of the method and algorithm proposed.


2012 ◽  
Vol 51 (17) ◽  
pp. 3811 ◽  
Author(s):  
Junpeng Xue ◽  
Xianyu Su ◽  
Liqun Xiang ◽  
Wenjing Chen

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