Ultra-wide baseline aerial imagery matching in urban environments
Research output: Contribution to conference › Paper › Research › peer-review
Correspondence matching is a core problem in computer vision. Under narrow baseline viewing conditions, this problem has been successfully addressed using SIFT-like approaches. However, under wide baseline viewing conditions these methods often fail. In this paper we propose a method for correspondence estimation that addresses this challenge for aerial scenes in urban environments. Our method creates synthetic views and leverages self-similarity cues to recover correspondences using a RANSAC-based approach aided by self-similarity graph-based sampling. We evaluate our method on 30 challenging image pairs and demonstrate improved performance to alternative methods in the literature.
Original language | English |
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Publication date | 2013 |
DOIs | |
Publication status | Published - 2013 |
Externally published | Yes |
Event | 2013 24th British Machine Vision Conference, BMVC 2013 - Bristol, United Kingdom Duration: 9 Sep 2013 → 13 Sep 2013 |
Conference
Conference | 2013 24th British Machine Vision Conference, BMVC 2013 |
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Country | United Kingdom |
City | Bristol |
Period | 09/09/2013 → 13/09/2013 |
Sponsor | Dyson, HP, IET Journals - The Institution of Engineering and Technology, Microsoft Research, Qualcomm |
ID: 302164635