A Stereo Selecting Method of Multi-view Matching Models Guided Based on Feature Points

JI Song; ZHANG Yongsheng; FAN Dazhao; GONG Zhihui

doi:10.13203/j.whugis20150458

Volume 43 Issue 1

Jan. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(1): 37-45. > DOI: 10.13203/j.whugis20150458

JI Song, ZHANG Yongsheng, FAN Dazhao, GONG Zhihui. A Stereo Selecting Method of Multi-view Matching Models Guided Based on Feature Points[J]. Geomatics and Information Science of Wuhan University, 2018, 43(1): 37-45. DOI: 10.13203/j.whugis20150458

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A Stereo Selecting Method of Multi-view Matching Models Guided Based on Feature Points

1.
Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China
2.
State Key Laboratory of Geo-Information Engineering, Xi'an 710054, China

Funds:

The National Natural Science Foundation of China 41401534

the Open Fund of State Key Laboratory of Geographic Information Engineering KLGIE2013-M-3-1

the Scientific Research Foundation for Public Welfare Industry of Surveying and Mapping and Geographic Information 201412007

More Information

Author Bio:
JI Song, PhD, lecturer, specializes in the theories and methods of multi-view matching and automatic DSM generation. E-mail: jisong_chxy@163.com
Corresponding author:
ZHANG Yongsheng, PhD, professor. E-mail:yszhang2001@vip.163.com
Received Date: January 31, 2016
Published Date: January 04, 2018

Graphical Abstract

Abstract

Abstract

Selecting one or more robust matching stereo pairs from redundant overlapping images to reduce the negative influence of incorrect or confusing image information to obtain the most desirable matching results improves multi-view matching ability and quality in multi-view matching techniques. In this paper, a matching quality analysis method for multi-view images is proposed that measures matching robustness based on correctly matched SIFT feature points. Furthermore, based on the method, a feature point guided multi-view image stereo selection matching method is detailed including the basic principles, algorithm, and matching process. Experiments were done on ADS40 multi-view imagery. The results show that the proposed method automatically and efficiently selects images of high matching quality from redundant overlapping images to obtain more correct multi-view matching results. This method is, to some extent, more effective than traditional multi-view matching methods.
- feature point,
- multi-view image,
- matching quality,
- matching measure,
- stereo selecting matching

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References (14)

References

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