Camera Calibration with Distortion Models and Accuracy Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
A Four-step Camera Calibration Procedure with Implicit Image Correction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Self-identifying patterns for plane-based camera calibration
Machine Vision and Applications
PROCAMS '08 Proceedings of the 5th ACM/IEEE International Workshop on Projector camera systems
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Calibration point extraction is an important step in camera calibration. Traditional methods work on single calibration board. In this paper, we propose a brand-new calibration point extraction algorithm that works on multiple calibration boards. In order to solve the world coordinate for every calibration point on multiple calibration boards, we propose a computable relation graph based algorithm. This algorithm constructs a computable relation graph with the computable relation between two calibration boards, and determines the computation order employing the classic minimum spanning tree algorithm. We use a triple parameter model to compute the position of one calibration board from another, and solve the problem by downhill simplex optimization. The proposed algorithm is fully automatic, and the precision is sufficiently high to fulfill the requirement of an image based modeling system.