Image Distortion and Rectification Calibration Algorithms and Validation Technique for a Stereo Camera

Kim, Jonguk; Bae, Hyansu; Lee, Suk Gyu

doi:10.3390/electronics10030339

Cited by 3 publications

(1 citation statement)

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“…In the existing literature, the traditional model [45][46][47][48] and division model [49,50] are widely used, and the division model is the most popular because it can result in simpler equation systems [5]. Depending on the number of parameters, the radial distortion models can be divided into one-parameter models [6,18,29,[51][52][53], two-parameter models [22,54], three-parameter models [35] and arbitrary parameter models [5,55]. According to the existing literature, it has been demonstrated that distortion is mainly dominated by the first two items [41].…”

Section: Introductionmentioning

confidence: 99%

A New Method for Absolute Pose Estimation with Unknown Focal Length and Radial Distortion

Guo

Chen

et al. 2022

Sensors

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Estimating the absolute pose of a camera is one of the key steps for computer vision. In some cases, especially when using a wide-angle or zoom lens, the focal length and radial distortion also need to be considered. Therefore, in this paper, an efficient and robust method for a single solution is proposed to estimate the absolute pose for a camera with unknown focal length and radial distortion, using three 2D–3D point correspondences and known camera position. The problem is decomposed into two sub-problems, which makes the estimation simpler and more efficient. The first sub-problem is to estimate the focal length and radial distortion. An important geometric characteristic of radial distortion, that the orientation of the 2D image point with respect to the center of distortion (i.e., principal point in this paper) under radial distortion is unchanged, is used to solve this sub-problem. The focal length and up to four-order radial distortion can be determined with this geometric characteristic, and it can be applied to multiple distortion models. The values with no radial distortion are used as the initial values, which are close to the global optimal solutions. Then, the sub-problem can be efficiently and accurately solved with the initial values. The second sub-problem is to determine the absolute pose with geometric linear constraints. After estimating the focal length and radial distortion, the undistorted image can be obtained, and then the absolute pose can be efficiently determined from the point correspondences and known camera position using the undistorted image. Experimental results indicate this method’s accuracy and numerical stability for pose estimation with unknown focal length and radial distortion in synthetic data and real images.

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