Polynomial Regression on Riemannian Manifolds

被引：0
|
作者：
Hinkle, Jacob [1 ]
Muralidharan, Prasanna [1 ]
Fletcher, P. Thomas [1 ]
Joshi, Sarang [1 ]
机构：
[1] Univ Utah, SCI Inst, Salt Lake City, UT 84112 USA
来源：
COMPUTER VISION - ECCV 2012, PT III | 2012年 / 7574卷
关键词：
FITTING SMOOTH PATHS; EQUATIONS; SPLINES;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we develop the theory of parametric polynomial regression in Riemannian manifolds. The theory enables parametric analysis in a wide range of applications, including rigid and non-rigid kinematics as well as shape change of organs due to growth and aging. We show application of Riemannian polynomial regression to shape analysis in Kendall shape space. Results are presented, showing the power of polynomial regression on the classic rat skull growth data of Bookstein and the analysis of the shape changes associated with aging of the corpus callosum from the OASIS Alzheimer's study.
引用
收藏
页码：1 / 14
页数：14
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