Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching

被引：338

作者：

Bronstein, AM ^{[1
]}

Bronstein, MM ^{[1
]}

Kimmel, R ^{[1
]}

机构：

[1] Technion Israel Inst Technol, Dept Comp Sci, IL-32000 Haifa, Israel

来源：

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | 2006年 / 103卷 / 05期

关键词：

Gromov-Hausdorff distance; isometric embedding; iterative-closest-point; partial embedding;

D O I：

10.1073/pnas.0508601103

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

An efficient algorithm for isometry-invariant matching of surfaces is presented. The key idea is computing the minimum-distortion mapping between two surfaces. For this purpose,we introduce the generalized multidimensional scaling, a computationally efficient continuous optimization algorithm for finding the least distortion embedding of one surface into another. The generalized multidimensional scaling algorithm allows for both full and partial surface matching. As an example, it is applied to the problem of expression-invariant three-dimensional face recognition.

引用

页码：1168 / 1172

页数：5

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