Deformation invariant image matching

TitleDeformation invariant image matching
Publication TypeConference Papers
Year of Publication2005
AuthorsLing H, Jacobs DW
Conference NameComputer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
Date Published2005/10//
Keywordsdeformation, deformations;nonaffine, deformations;point, descriptor;geodesic, distances;geodesic, geometry;differential, geometry;image, histogram;image, image, invariant, local, matching;computational, matching;deformation, matching;image, morphing;, sampling;geodesic-intensity

We propose a novel framework to build descriptors of local intensity that are invariant to general deformations. In this framework, an image is embedded as a 2D surface in 3D space, with intensity weighted relative to distance in x-y. We show that as this weight increases, geodesic distances on the embedded surface are less affected by image deformations. In the limit, distances are deformation invariant. We use geodesic sampling to get neighborhood samples for interest points, and then use a geodesic-intensity histogram (GIH) as a deformation invariant local descriptor. In addition to its invariance, the new descriptor automatically finds its support region. This means it can safely gather information from a large neighborhood to improve discriminability. Furthermore, we propose a matching method for this descriptor that is invariant to affine lighting changes. We have tested this new descriptor on interest point matching for two data sets, one with synthetic deformation and lighting change, and another with real non-affine deformations. Our method shows promising matching results compared to several other approaches