Factorization methods for structure from motion

被引:34
作者
Kanade, T [1 ]
Morris, DD [1 ]
机构
[1] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
来源
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 1998年 / 356卷 / 1740期
关键词
factorization; bilinear decomposition; Euclidean; affine; perspective;
D O I
10.1098/rsta.1998.0215
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
In this article we present an overview of factorization methods for recovering structure and motion from image sequences. We distinguish these methods from general nonlinear algorithms primarily by their bilinear formulation in motion and shape parameters. The bilinear formulation makes possible powerful and efficient solution techniques including singular value decomposition. We show how factorization methods apply under various affine camera models and under the perspective camera model, and then we review factorization methods for various features including points, lines, directional point features and line segments. An extension to these methods enables them to segment and recover motion and shape for multiple independently moving objects. Finally, we illustrate the generality of the factorization methods with two applications outside structure from motion.
引用
收藏
页码:1153 / 1171
页数:19
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