Kamgar-Parsi Behzad, Kamgar-Parsi Behrooz
Office of Naval Research, 800 N. Quincy St., Arlington, VA 22217, USA.
IEEE Trans Pattern Anal Mach Intell. 2004 May;26(5):582-93. doi: 10.1109/TPAMI.2004.1273930.
Matching two sets of lines is a basic tool that has applications in many computer vision problems such as scene registration, object recognition, motion estimation, and others. Line sets may be composed of infinitely long lines or finite length line segments. Depending on line lengths, three basic cases arise in matching sets of lines: 1) finite-finite, 2) finite-infinite, and 3) infinite-infinite. Case 2 has not been treated in the literature. For Cases 1 and 3, existing algorithms for matching 3D line sets are not completely satisfactory in that they either solve special situations, or give approximate solutions, or may not converge, or are not invariant with respect to coordinate system transforms. In this paper, we present new algorithms that solve exactly all three cases for the general situation. The algorithms are provably convergent and invariant to coordinate transforms. Experiments with synthetic and real 3D image data are reported.
匹配两组线是一种基本工具，在许多计算机视觉问题中都有应用，如场景配准、目标识别、运动估计等。线集可以由无限长的线或有限长度的线段组成。根据线的长度，在匹配线集时会出现三种基本情况：1）有限-有限，2）有限-无限，3）无限-无限。情况2在文献中尚未得到处理。对于情况1和3，现有的匹配3D线集的算法并不完全令人满意，因为它们要么解决特殊情况，要么给出近似解，要么可能不收敛，要么对于坐标系变换不是不变的。在本文中，我们提出了新的算法，这些算法能精确地解决一般情况下的所有三种情况。这些算法被证明是收敛的，并且对于坐标变换是不变的。报告了对合成和真实3D图像数据的实验。
