Method of solving intrinsic parameters of camera with regular pentagonal prismatic table

Abstract

The invention discloses a target used for self-calibrating of a camera and consisting of a regular prismatic table with regular pentagonal bottom surfaces. A method comprises the particular steps as follows: characteristic points on the upper bottom surface and the two side faces of the regular positive pentagonal prismatic table are extracted from an image; coordinates of vanishing points on a plane of the image are solved according to attributes that an intersection point of two parallel straight lines is an infinite point, and a simulacrum of the infinite point is the vanishing point, and according to the attribute of a cross ratio of four collinear points; intrinsic parameters of the camera are solved linearly according to constraint of the orthogonal vanishing points on an absolute conic; two images of the target are shot in different directions; the coordinates of the characteristic points on the images are extracted; the orthogonal vanishing points on the upper bottom surface and the two side faces of the regular positive pentagonal prismatic table are calculated; constraint equations of the orthogonal vanishing points relevant to the intrinsic parameters of the camera are established; and matrixes of the intrinsic parameters of the camera are solved linearly. With the adoption of the target, full automatic calibration can be realized, and errors due to measuring in a calibrating process are reduced. The vanishing points are more concise and global elements, and the accuracy is improved in the calibrating process.

Description

technical field [0001] The invention belongs to the field of computer research, and relates to a regular prism target whose base is a regular pentagon for solving internal parameters of a camera. Using any regular pentagon on a plane as a calibration template, the prism on two images is solved The coordinates of the orthogonal blanking point, linearly determine the internal parameters of the camera. Background technique [0002] One of the basic tasks of computer vision is to restore the geometric information of objects in three-dimensional space from the two-dimensional image information obtained by the camera, so as to recognize and reconstruct the geometric shape of objects in three-dimensional space. In this process, the relationship between the three-dimensional geometric position of the spatial object point and its corresponding point in the image must be determined, and this relationship is determined by the geometric model of the camera imaging, and the parameters of...

AI Technical Summary

Problems solved by technology

[0003] Although the traditional camera calibration method can obtain high precision, it is difficult to make the calibration block and it is not easy to operate. To solve this problem, the document "A flexible new technique for camera calibration", (Zhengyou Zhang, IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 22, no. 11, pp. 1330-1334, 2000.) proposed a method to replace the traditional calibration block with a flat template. The physical coordinates of the lattice on the positioning template, because the hidden point is a simpler and more global primitive, which can further improve the stability of the method, so it is widely used to solve the calibration problem with the hidden point, the literature "Criminisi A , Reid I. and A. Zisserman. Single View Metrology, International Journal of Computer Vision, 2000, 40 (2) , pp. 123- 148."Using the properties of vanishing points to calculate the internal parameters of the camera from a single projected image , this method for the first time integrates the vanishing point in projective geometry into the camera calibration, so the vanishing point becomes the theoretical basis of the camera self-calibration method

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