3D reconstruction based on the decomposition of matrix

被引：0

作者：

Wu, GY ^{[1
]}

Zhang, QB ^{[1
]}

Wangnian, W ^{[1
]}

机构：

[1] Anhui Univ, Key Lab Intelligent Comp & Signal Proc, Hefei 230039, Anhui, Peoples R China

来源：

THIRD INTERNATIONAL SYMPOSIUM ON MULTISPECTRAL IMAGE PROCESSING AND PATTERN RECOGNITION, PTS 1 AND 2 | 2003年 / 5286卷

关键词：

Kruppa equations; 3D reconstruction; SVD;

D O I：

10.1117/12.539017

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a 3D reconstruction method based on the decomposition of matrix. The method uses the Singular Value Decomposition (SVD) of the fundamental matrix, which leads to a particularly simple form of the Kruppa equations optimized by conjugate gradient method. The derivation doesn't need the somewhat non-intuitive geometric concept of the absolute conic. After the projective depths are estimated, the non-singular 4 x 4 matrix is obtained to realize the Euclidean reconstruction. Experimental results demonstrate the effectiveness of the proposed method.

引用

页码：208 / 211

页数：4