Abstract
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%.
Highlights
Measuring the distance between self and the obstacle is a crucial part of many fields. e type of method to measuring distance by cameras is called the vision-based ranging method, which may promote the development of automatic measurement and has a great research value [1, 2]. e vision-based ranging method includes the monocular vision-based ranging method and stereo vision-based ranging method
It is found that their distribution is not a simple linear distribution. erefore, to improve the accuracy of range, this study attempts to learn the distribution of focal length corresponding to different pixel positions by nonlinear regression. e results show that the method can effectively improve the accuracy of the ranging model
This study focuses on proposing a simple and high-accuracy camera’s focal length calibration method to improve the accuracy of the monocular vision-based ranging model. e major method is to use a simple linear imaging model to deduce the complexity of the ranging model and combine the distortion and defocusing phenomenon caused by the nonlinear imaging of the camera into the focal length calibration process. e main innovations of this study are as follows: (1) When the camera has an inclination angle in three dimensions, the ranging model for ground object based on the linear imaging model and geometric coordinate transformation is proposed
Summary
Measuring the distance between self and the obstacle is a crucial part of many fields. e type of method to measuring distance by cameras is called the vision-based ranging method, which may promote the development of automatic measurement and has a great research value [1, 2]. e vision-based ranging method includes the monocular vision-based ranging method and stereo vision-based ranging method. E type of method to measuring distance by cameras is called the vision-based ranging method, which may promote the development of automatic measurement and has a great research value [1, 2]. E vision-based ranging method includes the monocular vision-based ranging method and stereo vision-based ranging method. Stereo vision-based ranging methods use the parallax of cameras to measure, which needs to match multiple images taken by multiple cameras. Monocular vision-based ranging method has a higher performance than the stereo vision-based ranging method because it does not need match images in the data preprocessing stage [3]. Proportion-based methods are according to the principle that the distance is inversely proportional to the image’s size from the target in the image plane [4, 5].
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