使用自识别标记和SIFT关键点创建3D模型

M. Fiala, Chang Shu
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引用次数: 6

摘要

3D对象建模可以使用基准标记和/或特征检测器来完成。基准标记提供了高可靠性的检测,但是,不希望用标记覆盖要建模的对象。特征检测器可以找到图像之间的对应关系,但它们并不总是依赖于相机定位。提出了一种利用两者的优点自动生成物体三维模型并同步标定相机的方法。在阵列中使用自识别基准标记来定位每张图像的相机姿态,并使用SIFT特征来查找和匹配图像之间的目标特征。将三维SIFT点的Delaunay三角剖分形成的四面体雕刻到模型上。展示了一个系统,在该系统中,只需从具有未知内在参数的相机从不受控制的位置捕获一组图像,就可以自动生成放置在标记阵列上的物体的3D模型
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Model Creation Using Self-Identifying Markers and SIFT Keypoints
3D object modeling can be accomplished using fiducial markers and/or feature detectors. Fiducial markers provide high reliability of detection, however, it is undesirable to cover an object to be modeled with markers. Feature detectors can find correspondences between images but they cannot always be relied on to be usable for camera localization. A method is shown that uses the strengths of both to automatically create 3D models of object as well as simultaneously calibrating the camera. Self-identifying fiducial markers are used in arrays to localize the camera pose for each image and SIFT features are used to find and match object features between images. Tetrahedrons formed by Delaunay triangulation of the 3D SIFT points are carved to the model. A system is shown where 3D models are generated automatically of an object placed on a marker array simply by capturing a set of images from uncontrolled locations from a camera with unknown intrinsic parameters
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