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Calibration of non-overlapping cameras in vehicles

机译:车辆非重叠摄像机的校准

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Cameras are getting smaller and cheaper. So a cost-effective usage of multi-camera systems in vehicles gets more and more attractive. In many cases it is desirable to cover the whole environment all around the vehicle. But often design restrictions and energy consumption do not allow constellations of cameras with overlapping field of views. However, for a common and geometric usage of the extracted information, e. g. in structure from motion tasks, it is necessary to know the relative alignment of the cameras, which are the extrinsic calibration parameters. This paper adresses the extrinsic calibration of a multi camera rig with non-overlapping field of views on a mobile platform. As the field of views do not necessarily overlap, common calibration methods based on corresponding image points between the camera views will fail. This problem can be overcome by using the mobiltiy of the platform. A pattern-based method for extrinsic calibration of the camera rig on a mobile plattform is presented.
机译:相机越来越小,越来越便宜。因此,在车辆中以经济高效的方式使用多摄像头系统变得越来越有吸引力。在许多情况下,希望覆盖车辆周围的整个环境。但是通常设计限制和能源消耗不允许具有重叠视场的摄像机群。但是,对于提取的信息的通用和几何用法,例如。 G。在运动任务的结构中,有必要知道摄像机的相对对准,这是外部校准参数。本文介绍了在移动平台上具有非重叠视场的多摄像头装置的外部校准。由于视场不一定重叠,因此基于相机视点之间相应图像点的常规校准方法将失败。通过使用平台的移动性可以解决此问题。提出了一种基于模式的移动平台上相机架外部校准的方法。

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