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Another Way of Looking at Plane-Based Calibration: The Centre Circle Constraint

机译:查看平面校准的另一种方式:中心圈约束

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The plane-based calibration consists in recovering the internal parameters of the camera from the views of a planar pattern with a known geometric structure. The existing direct algorithms use a problem formulation based on the properties of basis vectors. They minimize algebraic distances and may require a 'good' choice of system normalization. Our contribution is to put this problem into a more intuitive geometric framework. A solution can be obtained by intersecting circles, called Centre Circles, whose parameters are computed from the world-to-image homographies. The Centre Circle is the camera centre locus when planar figures are in perpective correspondence, in accordance with a Poncelet's theorem. An interesting aspect of our formulation, using the Centre Circle constraint, is that we can easily transform the cost function into a sum of squared Euclidean distances. The simulations on synthetic data and an application with real images confirm the strong points of our method.
机译:平面的校准包括从平面图案的视图中恢复相机的内部参数,具有已知几何结构。现有的直接算法基于基础向量的性质使用问题配方。它们最小化代数距离,可能需要“良好”的系统归一化选择。我们的贡献是将此问题放入更直观的几何框架中。通过与圆圈相交的圆圈,称为中心圆圈可以获得解决方案,其参数从世界到图像沉默计算。根据Poncelet的定理,中心圈是当平面图以相对应的相对应的时圈。我们配方的一个有趣方面,使用中心圈限制,是我们可以轻松地将成本函数转换为平方欧几里德距离的总和。对合成数据的模拟和实际图像的应用确认了我们方法的强点。

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