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Re-calibration of camera space manipulation techniques accounting for fisheye lens radial distortion

机译:用于Camera Space操作技术的重新校准用于Fisheye镜头径向畸变的核算

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We explore the possibility to use Linear Camera Space manipulation (LCSM) algorithm [1] to map a large workspace using cameras equipped with fisheye lenses. We tested how the distortion of the image caused by the lens influences the precision of the LCSM algorithm when used to estimate the positions of visual cues in 3-D space. We used two Hero3 GoPro? (H3GP) cameras as a good compromise between acquisition rate and number of pixel in the image. We used a previously published correction algorithm to eliminate the fisheye distortion [2] and compare it with standard calibration. The model estimate the radial distortion with a bi-quadratic equation which coefficients K and K2To estimate such coefficients a non-linear calibration called Stereo Calibration Method was also used [2]. Stereo calibration uses a pair of images, also known as a stereo pair, to estimate the relative depth of points in the scene. These estimates are represented in a stereo disparity map, which is constructed by matching corresponding points within the stereo pair. These coordinates are used to calculate the distortion factors of each camera lens.
机译:我们探讨了使用线性摄像机空间操作(LCSM)算法[1]使用配备有鱼眼镜头的摄像机映射大工作区的可能性。我们测试了镜头引起的图像的失真如何影响LCSM算法的精度,用于估计3-D空间中的视觉线索的位置。我们使用了两个英雄3 gopro? (H3GP)相机作为图像中采集率和像素数之间的良好折衷。我们使用先前发布的校正算法来消除鱼眼失真[2]并将其与标准校准进行比较。模型估计与系数k和k的双二次方程的径向失真 2 为了估计这种系数,也使用了称为立体声校准方法的非线性校准[2]。立体声校准使用一对图像,也称为立体对,以估计场景中的相对深度。这些估计在立体声差异图中表示,其通过匹配立体对内的对应点来构造。这些坐标用于计算每个摄像机镜头的失真因子。

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