Method of Calibrating Pinhole Camera Using Common Self-polar Triangle

Abstract

The invention is a method for calibrating a pinhole camera by using a common self-polar triangle. First, extract the edge points of the target image from this image respectively, and use the least square method to fit to obtain three spherical image equations. According to the fact that any two separated spherical images have a unique common self-polar triangle, a set of corresponding poles and epipolar lines of the two spherical images can be obtained. At the same time, this epipolar line is the image passing through the center of the two spheres, so according to the relationship between the spherical image and the image of the absolute dual conic curve, the constraint relationship between the image of the absolute quadratic curve and the common pole and the epipolar line can be obtained, thus Obtain the image of the absolute conic curve, and solve the internal parameters of the pinhole camera.

Description

technical field [0001] The invention belongs to the field of computer vision and relates to a method for solving internal parameters of a pinhole camera by using a spherical image in space and a common self-polar triangle. Background technique [0002] The central task of computer vision is to understand images, and its ultimate goal is to enable computers to have the ability to recognize three-dimensional environmental information through two-dimensional images. This ability will not only enable the machine to perceive the geometric information of objects in a three-dimensional environment including shape, posture, motion, etc., but also describe, store, recognize and understand them. Camera calibration is to determine the mapping relationship from a three-dimensional space point to its two-dimensional image point, which is an essential step in many computer vision applications. In order to determine this mapping process, it is necessary to establish a geometric imaging mo...

AI Technical Summary

Problems solved by technology

The document "An algorithm for self-calibration from several views", (R. Hartley., In Proc. IEEE Conference on Computer Vision and Pattern Recognition, pages 908–912, June 1994.) proposed a pinhole camera self-calibration method, The advantage of this type of method is that there is no need to use a calibration block, and the disadvantage is that the corresponding points between images must be obtained

In computer vision, it is very difficult to implement a very effective method for finding corresponding points.

The literature "A new easy camera calibration technique based on circular points", (Meng, X., Hu, Z., Pattern Recognition, 2003, 36(5): 1155-1164.) proposes to use a circle and pass through a pinhole camera Several branch lines at the center of the circle are used as calibration templates. The advantage of this method is that the vanishing point can be obtained by linear solution, but the image of the circle point cannot be directly obtained, and there will be redundant straight lines, resulting in greater error

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