TY - CONF

T1 - Ultra-wide baseline aerial imagery matching in urban environments

AU - Altwaijry, Hani

AU - Belongie, Serge

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84898463143&partnerID=8YFLogxK

U2 - 10.5244/C.27.15

DO - 10.5244/C.27.15

M3 - Paper

AN - SCOPUS:84898463143

T2 - 2013 24th British Machine Vision Conference, BMVC 2013

Y2 - 9 September 2013 through 13 September 2013

ER -