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An automatic self-calibration approach for wide baseline stereo cameras using sea surface images

机译:使用海面图像的宽基线立体相机的自动自校准方法

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The calibration process of a stereo rig is normally done by making two cameras view one special designed calibration pattern (such as checkerboard) at the same time to estimate the relative rotation between two cameras. Multiple image pairs from different perspectives are required for better estimation accuracy. Stereo rig with wide baseline is necessary when accurate depth estimation for distant object is desired. However, in order to make calibration pattern to be viewed from both left and right cameras, the wider the baseline the bigger the calibration pattern should be. Manpower even equipment such as crane is required to operate such a big checkerboard for the calibration purpose only. In contrast to the traditional stereo calibration method using calibration pattern, we propose a self-calibration approach that can easily estimate cameras' rotation matrices for stereo rig with very wide baseline using sea horizon and a point at infinite distance. Compared with conventional techniques which require expensive equipments or manpower, our approach only needs a pair of sea images, moreover, special calibration patterns and feature correspondences are not required. As a result, it is flexible and very easy to implement. Real world experiments demonstrate the feasibility of our approach.
机译:立体声钻机的校准过程通常是通过使两个摄像机同时查看一个特殊设计的校准图案(例如棋盘格)来估计两个摄像机之间的相对旋转来完成的。需要来自不同角度的多个图像对,以实现更好的估计精度。当需要对远处物体进行精确的深度估算时,必须使用具有宽基线的立体声装置。但是,为了使左右相机都能看到校准图案,基线越宽,校准图案应该越大。甚至需要诸如起重机之类的人力设备来操作如此大的棋盘,仅用于校准目的。与使用校准模式的传统立体声校准方法相比,我们提出了一种自校准方法,该方法可以轻松估计摄像机的旋转矩阵,该摄像机具有非常宽的基线(使用海平面和无限远的点)。与需要昂贵设备或人力的常规技术相比,我们的方法仅需要一对海图,而且不需要特殊的校准图案和特征对应。结果,它是灵活的并且非常容易实现。实际实验证明了我们方法的可行性。

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