Point Feature Matching
Point Feature Matching is a computational method in multi-view geometry that identifies corresponding image points across different views by establishing geometric and photometric consistency, distinguishing itself from other correspondence techniques through its reliance on localized, distinctive feature descriptors invariant to viewpoint and illumination changes.
264
Publications
12.7K
Citations
819
Authors
321
Institutions
Publications per year
2017–2026
76
Variants
Point Correspondence
Parents
264
Model globally, match locally: Efficient and robust 3D object recognition
Bertram Drost, Markus Ulrich, Nassir Navab et al. · 2010 · 982 citations
A fast local descriptor for dense matching
Engin Tola, Vincent Lepetit, Pascal Fua · 2008 · 485 citations · Full text
A SIFT Descriptor with Global Context
Eric N. Mortensen, Hongli Deng, Linda G. Shapiro · 2005 · 252 citations
Multiview Clustering via Adaptively Weighted Procrustes
Feiping Nie, Lai Tian, Xuelong Li · 2018 · 247 citations · Full text
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321
Wuhan University
Wuhan, China
9 h-index
34 publications
1.5K citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
7 h-index
22 publications
1K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
7 h-index
15 publications
551 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
27 publications
848 citations

Beihang University
Beijing, China
6 h-index
21 publications
687 citations
University of Chinese Academy of Sciences
Beijing, China
6 h-index
18 publications
527 citations
Massachusetts Institute of Technology
Cambridge, United States
5 h-index
8 publications
817 citations
Technical University of Munich
Munich, Germany
5 h-index
9 publications
2.2K citations
1–8 of 321
TPAMI · 16 publications · 1.5K citations
16
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11 publications · 623 citations
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11 publications · 281 citations
11
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6 publications · 112 citations
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6 publications · 162 citations
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