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Auto-Calibration Method to Determine Camera Pose for Stereovision-Based Off-Road Vehicle Navigation

机译:确定基于立体视觉的越野车辆导航摄像机姿态的自动校准方法

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摘要

Stereo cameras have been used as perception sensors for agricultural vehicle navigation for years. One problem impeding their broader application is the difficulty of calibrating the installation poses of a camera using conventional measuring tools, especially when such a system is used in ill-structured agricultural field environments. The research reported in this paper was aimed to develop an automated calibration method for determining the camera installation pose with respect to a vehicle frame. Based on this method, a binocular stereo camera acquired a sequence of field scenery images as the vehicle moved straight forward for a short distance on a relatively flat surface. An image processing algorithm has been developed to detect some static feature points in the ground image and track their three-dimensional (3D) relative motions with respect to the moving vehicle. A plane best fitting to those detected ground features was then used to determine the camera roll and pitch angles, and the tracked motions of those feature points were used to estimate the camera yaw. Field test results validated that the developed auto-calibration method was capable of determining the camera installation pose at a calibration accuracy of ±1° over an approximately 10 m of vehicle traveling distance. The calibrated poses could be used to compensate for the navigation errors induced by camera misalignment.
机译:多年以来,立体声相机已被用作农用车辆导航的感知传感器。阻碍其广泛应用的一个问题是难以使用常规测量工具来校准照相机的安装姿势,尤其是当这种系统用于结构不良的农田环境时。本文报道的研究旨在开发一种自动校准方法,用于确定相对于车架的摄像机安装姿势。基于此方法,当车辆在相对平坦的表面上笔直向前移动一小段距离时,双目立体摄像机会获取一系列的现场风景图像。已经开发了一种图像处理算法来检测地面图像中的一些静态特征点,并跟踪它们相对于移动车辆的三维(3D)相对运动。然后,使用最适合那些检测到的地面特征的平面来确定相机的侧倾角和俯仰角,并使用这些特征点的跟踪运动来估算相机的偏航角。现场测试结果证明,开发的自动校准方法能够在大约10 m的车辆行驶距离内以±1°的校准精度确定摄像机的安装姿势。校准的姿势可用于补偿由相机未对准引起的导航误差。

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