A Novel Image Points Matching Method by Intersecting into Space for Close-range Photogrammetry

被引：0

作者：

Long Changyu ^{[1
,2
]}

Liu Guangtong ^{[1
,2
]}

Zhang Bin ^{[1
,2
]}

Ruan Guowei ^{[1
,2
]}

Zhang Chengli ^{[1
,2
]}

Tao Li ^{[1
,2
]}

Wang Ziwen ^{[1
,2
]}

Wang Wei ^{[1
,2
]}

Zhang Yuhang ^{[1
,2
]}

机构：

[1] Beijing Inst Spacecraft Environm Engn, Beijing 100094, Peoples R China

[2] Beijing Engn Res Ctr Intelligent Assembly Technol, Beijing 100094, Peoples R China

来源：

2019 INTERNATIONAL CONFERENCE ON OPTICAL INSTRUMENTS AND TECHNOLOGY: OPTOELECTRONIC MEASUREMENT TECHNOLOGY AND SYSTEMS | 2020年 / 11439卷

基金：

中国国家自然科学基金;

关键词：

image points matching; close-range photogrammetry; epipolar geometry; spatial intersection; FUNDAMENTAL MATRIX;

D O I：

10.1117/12.2542374

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

Image points matching between multiple uncalibrated images has always been an important task in Close-range photogrammetry and difficulties are often experienced. Epipolar geometry constraint method is considered to be an effective way to solve this problem and it has been studied in detail. However, large amount of applications have shown that epipolar geometry is hard to be recovered accurately due to image distortion and positioning error, which leads to numerous mismatches when image points are distributed intensively. In order to solve this problem, an alternative image points matching technique to the epipolar geometry constraint method is investigated, which matches the image points combining with a bundle adjustment process and using their corresponding spatial collinear lines intersected on 3D space instead of finding on 2D epipolar line. In this paper, the matching principle and process of this method are described in detail. Experiment results and comparison with epipolar geometry constraint method are displayed, which verifies the flexibility and effectiveness of this method.

引用

页数：14

共 17 条

[1]

[Anonymous], 2008, 2008 IEEE C COMP VIS

[2] Overall view regarding fundamental matrix estimation [J].

Armangué, X ;

Salvi, J .

IMAGE AND VISION COMPUTING, 2003, 21 (02) :205-220

[3]

Bourke P., 2010, ERESEARCH AUSTRALASI

[4]

Carro A. I., 2012, 3DTV C IEEE, P1

[5] Why not use the Levenberg-Marquardt method for fundamental matrix estimation? [J].

Chen, P. .

IET COMPUTER VISION, 2010, 4 (04) :286-294

[6]

Duan J., 2013, APPL MECH MAT, V347, P3624

[7] A hybrid measurement approach for close-range photogrammetry [J].

Fraser, Clive S. ;

Cronk, Simon .

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2009, 64 (03) :328-333

[8] A Robust Feature Matching Approach for Photography Originality Test [J].

Gao, Ce ;

Song, Yixu ;

Jia, Peifa .

JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2012, 44 (02) :185-194

[9]

Kanatani K., 2011, MEMOIRS FACULTY ENG, V45, P27

[10]

Long C., 2014, J INFORM COMPUTATION, V11, P15

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