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Static Camera Calibration for Advanced Driver Assistance System Used in Trucks - Robust Detector of Calibration Points

机译:用于卡车的高级驾驶员辅助系统的静态摄像机校准-坚固的校准点检测器

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The paper presents selected investigation results on a static (factory) calibration procedure of the camera, for the use in Advanced Driver Assistance System (ADAS) mounted in trucks. It is a commercial project that has already been put for production. For this reason, special emphasis was put on the reliability of the proposed solutions. Additionally, the developed algorithms were optimized so that all computations are completed within an assumed period of time (requirements). One of the problems encountered during the development of the calibration procedure was the fact that various objects were located around the calibration pattern in the factory. In some situations these objects may be classified as calibration points, resulting in false outcomes of the overall calibration procedure. For this reason, special emphasis was placed on the development of appropriate robust algorithms responsible for the detection of calibration points. For example, the implemented methods allow for distinguishing the false points and removing them from the list of detected points. The overall procedure was carefully tested under various conditions, including unfavorable ones, with more than 500,000 tests.
机译:本文介绍了针对照相机的静态(出厂)校准程序的选定研究结果,以供安装在卡车上的高级驾驶员辅助系统(ADAS)使用。这是一个已经投入生产的商业项目。因此,特别强调了所提出解决方案的可靠性。此外,对开发的算法进行了优化,以使所有计算都在假定的时间段内完成(要求)。校准程序开发过程中遇到的问题之一是,工厂中在校准图案周围放置了各种物体。在某些情况下,这些对象可能被归类为校准点,从而导致整个校准过程的错误结果。由于这个原因,特别强调了负责检测标定点的适当鲁棒算法的开发。例如,所实现的方法允许区分错误点并将错误点从检测到的点列表中移除。在各种条件下(包括不利条件),对整个过程进行了仔细的测试,进行了超过500,000次测试。

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