[{"data":1,"prerenderedAt":70},["ShallowReactive",2],{"post-66d4364b":3},{"abbrlink":4,"title":5,"date":6,"categories":7,"tags":9,"excerpt":11,"html":12,"toc":13},"66d4364b","使用平行线段的相机标定[计划更新]","2022-04-16",[8],"图像处理",[10],"论文复现","摘要 一种使用平行线段来进行相机标定以及形状重建的方法","\u003Ch2 id=\"post-heading-摘要\">摘要\u003C\u002Fh2>\n\u003Cp>一种使用平行线段来进行相机标定以及形状重建的方法\u003C\u002Fp>\n\u003Ch2 id=\"post-heading-介绍\">介绍\u003C\u002Fh2>\n\u003Cp>监控摄像机标定一直是计算机视觉工业应用的一个重要课题。内部和外部参数都必须精确校准，才能从记录的 2D 图像或视频中识别出 3D 场景中发生的事情，相机标定的一般方法是使用标定对象，如棋盘标定。然而，这些方法对于监控摄像机来说往往是不切实际的，因为它们需要一个足够大的校准对象来覆盖整个拍摄区域。\u003C\u002Fp>\n\u003Cblockquote>\n\u003Cp>源码：\u003Ca href=\"https:\u002F\u002Fgithub.com\u002FEmanueleGhelfi\u002Fiacv\" target=\"_blank\" rel=\"noopener noreferrer\">https:\u002F\u002Fgithub.com\u002FEmanueleGhelfi\u002Fiacv\u003C\u002Fa>\u003C\u002Fp>\n\u003C\u002Fblockquote>\n\u003Ch2 id=\"post-heading-直线提取\">直线提取\u003C\u002Fh2>\n\u003Ch3 id=\"post-heading-canny\">Canny\u003C\u002Fh3>\n\u003Ch3 id=\"post-heading-hough-transform\">Hough Transform\u003C\u002Fh3>\n\u003Ch2 id=\"post-heading-形状重建\">形状重建\u003C\u002Fh2>\n\u003Ch3 id=\"post-heading-affine-rectification\">Affine Rectification\u003C\u002Fh3>\n\u003Ch3 id=\"post-heading-euclidean-rectification\">Euclidean Rectification\u003C\u002Fh3>\n\u003Ch2 id=\"post-heading-度量指标属性\">度量指标属性\u003C\u002Fh2>\n\u003Ch2 id=\"post-heading-相机标定\">相机标定\u003C\u002Fh2>\n\u003Ch2 id=\"post-heading-世界坐标定位\">世界坐标定位\u003C\u002Fh2>\n\u003Ch2 id=\"post-heading-3d-形状重构\">3D 形状重构\u003C\u002Fh2>\n\u003Ch2 id=\"post-heading-实现细节\">实现细节\u003C\u002Fh2>\n\u003Ch3 id=\"post-heading-fitting-vanishing-point\">Fitting Vanishing Point\u003C\u002Fh3>\n\u003Ch3 id=\"post-heading-fitting-line-at-infinity\">Fitting Line at Infinity\u003C\u002Fh3>\n\u003Ch3 id=\"post-heading-fitting-conics\">Fitting Conics\u003C\u002Fh3>\n\u003Ch2 id=\"post-heading-总结分析\">总结分析\u003C\u002Fh2>\n\u003Ch2 id=\"post-heading-计算结果\">计算结果\u003C\u002Fh2>\n",[14,18,21,24,28,31,34,37,40,43,46,49,52,55,58,61,64,67],{"id":15,"text":16,"level":17},"post-heading-摘要","摘要",2,{"id":19,"text":20,"level":17},"post-heading-介绍","介绍",{"id":22,"text":23,"level":17},"post-heading-直线提取","直线提取",{"id":25,"text":26,"level":27},"post-heading-canny","Canny",3,{"id":29,"text":30,"level":27},"post-heading-hough-transform","Hough Transform",{"id":32,"text":33,"level":17},"post-heading-形状重建","形状重建",{"id":35,"text":36,"level":27},"post-heading-affine-rectification","Affine Rectification",{"id":38,"text":39,"level":27},"post-heading-euclidean-rectification","Euclidean Rectification",{"id":41,"text":42,"level":17},"post-heading-度量指标属性","度量指标属性",{"id":44,"text":45,"level":17},"post-heading-相机标定","相机标定",{"id":47,"text":48,"level":17},"post-heading-世界坐标定位","世界坐标定位",{"id":50,"text":51,"level":17},"post-heading-3d-形状重构","3D 形状重构",{"id":53,"text":54,"level":17},"post-heading-实现细节","实现细节",{"id":56,"text":57,"level":27},"post-heading-fitting-vanishing-point","Fitting Vanishing Point",{"id":59,"text":60,"level":27},"post-heading-fitting-line-at-infinity","Fitting Line at Infinity",{"id":62,"text":63,"level":27},"post-heading-fitting-conics","Fitting Conics",{"id":65,"text":66,"level":17},"post-heading-总结分析","总结分析",{"id":68,"text":69,"level":17},"post-heading-计算结果","计算结果",1792849565660]