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Linear Pose Estimation from Points or Lines

机译:点或线的线性姿态估计

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Estimation of camera pose from an image of n points or lines with known correspondence is a thoroughly studied problem in computer vision. Most solutions are iterative and depend on nonlinear optimization of some geometric constraint, either on the world coordinates or on the projections to the image plane. For real-time applications we are interested in linear or closed-form solutions free of initialization. We present a general framework which allows for a novel set of linear solutions to the pose estimation problem for both n points and n lines. We present a number of simulations which compare our results to two other recent linear algorithm as well as to iterative approaches. We conclude with tests on real imagery in an augmented reality setup. We also present an analysis of the sensitivity of our algorithms to image noise.
机译:来自N个点或具有已知对应关系的图像的相机姿势的估计是计算机视觉中的彻底研究问题。大多数解决方案都是迭代的,并取决于一些几何约束的非线性优化,无论是世界坐标还是对图像平面的投影。对于我们的实时应用程序,我们对Linear或封闭式解决方案感兴趣,无初始化。我们展示了一般框架,它允许对N个点和n行的姿势估计问题进行新颖的线性解决方案。我们提出了许多模拟,将我们的结果与另外两种最近的线性算法进行比较,以及迭代方法。我们结束了在增强现实设置中的真实图像上的测试。我们还展现了对图像噪声的算法的敏感性分析。

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