人工智能
计算机视觉
摄像机自动校准
摄像机切除
焦距
校准
像素
针孔相机模型
测距
单眼
计算机科学
职位(财务)
摄像机矩阵
数学
光学
物理
镜头(地质)
统计
经济
电信
财务
作者
Lixia Xue,Meian Li,Liang Fan,Aixia Sun,Tian Gao
摘要
The camera calibration in monocular vision represents the relationship between the pixels’ units which is obtained from a camera and the object in the real world. As an essential procedure, camera calibration calculates the three-dimensional geometric information from the captured two-dimensional images. Therefore, a modified camera calibration method based on polynomial regression is proposed to simplify. In this method, a parameter vector is obtained by pixel coordinates of obstacles and corresponding distance values using polynomial regression. The set of parameter’s vectors can measure the distance between the camera and the ground object in the field of vision under the camera’s posture and position. The experimental results show that the lowest accuracy of this focal length calibration method for measurement is 97.09%, and the average accuracy was 99.02%.
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