网络安全与数据治理2025，Vol.44Issue(4)：46-51,6.DOI:10.19358/j.issn.2097-1788.2025.04.007
应用于相机标定的亚像素棋盘角点检测
Subpixel checkerboard corner detection for camera calibration
摘要
Abstract
In the camera calibration process,the accuracy of chessboard corner detection is crucial for ensuring the precision of calibration results.Addressing the insufficient accuracy of current chessboard corner detection methods,this study proposes a no-vel sub-pixel level chessboard corner detection technique.Firstly,the U-Net convolutional neural network is employed as the backbone network to construct corner heatmaps based on the captured chessboard images.In addition,in order to reduce the se-mantic gap between encoder and decoder features,this research innovatively introduces a channel and spatial dual-cross attention module.Subsequently,precise sub-pixel chessboard corner coordinates are calculated using a Gaussian surface fitting method.Experimental results demonstrate that this method effectively improves the accuracy of corner detection and achieves lower repro-jection error in camera calibration tasks.关键词
相机标定/角点检测/通道和空间交叉注意力/卷积神经网络Key words
camera calibration/corner detection/channel and spatial cross-attention/convolutional neural network分类
信息技术与安全科学引用本文复制引用
陈泽勇,吴丽君,李乙..应用于相机标定的亚像素棋盘角点检测[J].网络安全与数据治理,2025,44(4):46-51,6.基金项目
国家自然科学基金(62271151,W2421092) （62271151,W2421092）
