计算机视觉
人工智能
失真(音乐)
摄像机切除
计算机科学
摄像机自动校准
校准
图像校正
投影(关系代数)
数码相机
重射误差
点(几何)
针孔相机模型
消失点
整改
图像(数学)
数学
算法
工程类
统计
电气工程
计算机网络
电压
放大器
带宽(计算)
几何学
作者
Ziyi Jin,Zhixue Li,Tianyuan Gan,Zuoming Fu,Chongan Zhang,Zhongyu He,Hong Zhang,Peng Wang,Jiquan Liu,Xuesong Ye
出处
期刊:Sensors
[MDPI AG]
日期:2022-05-05
卷期号:22 (9): 3524-3524
被引量:5
摘要
The camera is the main sensor of vison-based human activity recognition, and its high-precision calibration of distortion is an important prerequisite of the task. Current studies have shown that multi-parameter model methods achieve higher accuracy than traditional methods in the process of camera calibration. However, these methods need hundreds or even thousands of images to optimize the camera model, which limits their practical use. Here, we propose a novel point-to-point camera distortion calibration method that requires only dozens of images to get a dense distortion rectification map. We have designed an objective function based on deformation between the original images and the projection of reference images, which can eliminate the effect of distortion when optimizing camera parameters. Dense features between the original images and the projection of the reference images are calculated by digital image correlation (DIC). Experiments indicate that our method obtains a comparable result with the multi-parameter model method using a large number of pictures, and contributes a 28.5% improvement to the reprojection error over the polynomial distortion model.
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