A Family of Simplified Geometric Distortion Models for Camera Calibration
Lili Ma, YangQuan Chen, Kevin L. Moore
Abstract
The commonly used radial distortion model for camera calibration is in fact an assumption or a restriction. In practice, camera distortion could happen in a general geometrical manner that is not limited to the radial sense. This paper proposes a simplified geometrical distortion modeling method by using two different radial distortion functions in the two image axes. A family of simplified geometric distortion models is proposed, which are either simple polynomials or the rational functions of polynomials. Analytical geometric undistortion is possible using two of the distortion functions discussed in this paper and their performance can be improved by applying a piecewise fitting idea. Our experimental results show that the geometrical distortion models always perform better than their radial distortion counterparts. Furthermore, the proposed geometric modeling method is more appropriate for cameras whose distortion is not perfectly radially symmetric around the center of distortion.
Create a lesson
Related papers
Selective Event Evidence and Persistent Temporal Priors for Event-Based Point Tracking
Xiaokai Song, Zhang Li, Leqi Liu et al.
Fast and Accurate Hand Estimation in Pixels, Interaction and World Space
Jinkun Cao
AffineGS: Unlocking Accurate Geometry in 3DGS via Spatially Varying Affine Rectification
Tze Ho Elden Tse, Jizong Peng, Richard Chen et al.
FlyingDrones: A Dataset and Benchmark for Optical Flow Estimation from UAV motion
Laurenz Ruzicka, Roman Pflugfelder, Daniel Cremers
InfMasking: A Unified Variational Framework for Synergistic Multimodal Learning
Liangjian Wen, Qun Dai, Jiang Duan et al.
ReferClaw: Disambiguating User Intent for Egocentric Assistance
Hangyu Qin, Junbin Xiao, Angela Yao