距离图像中表面形状的表示和识别:微分几何方法

Ping Liang , John S. Todhunter
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引用次数: 61

摘要

提出了在距离图像中精确定位和识别三维表面形状的理论和匹配算法。证明了曲面理论基本理论的两个推论。第一个推论证明了曲率线作为本征参数曲线时基本系数的不变性。第二个推论证明了除了保持形状算子(Weingarten映射)的特征向量和特征值外,保持沿主方向的固有距离的微分同构必然是等距的。基于这两个推论,从理论上确定了一组满足唯一性和不变性要求的几何描述子,适用于所有类型的曲面,即双曲曲面、椭圆曲面和可展曲面。提出了单元法线和形状描述符列表数组(UNSDLA)表示及其匹配算法。UNSDLA是对扩展高斯图像(EGI)的推广。EGI有一个基本的限制;也就是说,它只能唯一地表示凸形状。新的表示法克服了EGI的这一限制,并将唯一表示法的范围扩展到所有类型的曲面。此外,它仍然具有EGI的所有优点。这是通过保留原始数据的连通性来实现的。这里的连通性不仅包括表面上点或斑块的邻接关系,还包括点或斑块在连接路径中穿越的方向和顺序。强调互联互通方向和秩序的重要性。使用UNSDLA可以比EGI更精确地进行表面匹配。基于UNSDLA表示,曲面可以通过高斯映射通过优化曲面形状的所有可能旋转来匹配。该表示与匹配算法可以处理高斯映射不是一一对应的双曲曲面和椭圆曲面。对于主曲率为非零的曲率线的高斯映射不是一一对应的可展曲面也可以被容纳。证明了可展曲面上的两个定理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Representation and recognition of surface shapes in range images: A differential geometry approach

Theory and matching algorithms are developed for accurate orientation determination and recognition of 3D surface shapes in range images. Two corollaries to the fundamental theory of surface theory are proved. The first corollary proves the invariance of the fundamental coefficients when lines of curvature are used as the intrinsic parameter curves. The second corollary proves that a diffeomorphism which preserves the intrinsic distance along the principal directions, in addition to preserving the eigenvectors and eigenvalues of the shape operator (Weingarten map), is necessarily an isometry. Based on these two corollaries, a set of geometric descriptors which satisfy the uniqueness and invariance requirements are theoretically identified for all classes of surfaces, namely, hyperbolic, elliptic, and developable surfaces. Theunit normal and shape descriptors list array (UNSDLA) representation and the corresponding matching algorithm are developed. The UNSDLA is a generalization of the extended Gaussian image (EGI). The EGI has a fundamental limitation; that is, it can only uniquely represent convex shapes. The new representation overcomes this limitation of the EGI and extends the scope of unique representation to all classes of surfaces. Moreover, it still has all the advantages of the EGI. This is achieved by preserving the connectivity of the original data. Connectivity here should include not only the adjacency relation of points or patches on a surface, but also the direction and order in which the points or patches are traversed in a connected path. The importance of the direction and order of connectivity is emphasized. Surface matching can be performed more accurately using the UNSDLA than the EGI. Based on the UNSDLA representations, surfaces can be matched via the Gaussian map by optimization over all possible rotations of a surface shape. The representation and matching algorithm can deal with hyperbolic and elliptic surfaces whose Gaussian maps are not one-to-one. Developable surfaces whose Gaussian maps of lines of curvature with nonzero principal curvature are not one-to-one can also be accommodated. Two theorems on developable surfaces are proved.

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