Using vanishing points for camera calibration
International Journal of Computer Vision
An introduction to differential evolution
New ideas in optimization
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Euclidean Reconstruction from Uncalibrated Views
Proceedings of the Second Joint European - US Workshop on Applications of Invariance in Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Camera Calibration with One-Dimensional Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Geometric Constraints through Parallelepipeds for Calibration and 3D Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
A comparative study of differential evolution variants for global optimization
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
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In this article we propose a new method to calibrate directly the camera by which it was taken an image of a cuboid, and to find at the same time the orientation and side lengths of the cuboid. This is a highly non-linear optimization problem that is solved directly using a heuristic called differential evolution. We show in this paper that this problem is very difficult if one tries to solve it with a conventional scalar optimization procedure. Although differential evolution is a heuristic, we find valid results in 100% of the executions. We test our method with synthetic and real images.