Wide-Baseline Image Matching Using Line Signatures

Abstract

We present a wide-baseline image matching approach based on line segments. Line segments are clustered into local groups according to spatial proximity. Each group is treated as a feature called a Line Signature. Similar to local features, line signatures are robust to occlusion, image clutter, and viewpoint changes. The descriptor and similarity measure of line signatures are presented. Under our framework, the feature matching is not only robust against affine distortion but also a considerable range of 3D viewpoint changes for non-planar surfaces. When compared to matching approaches based on existing local features, our method shows improved results with low-texture scenes. Moreover, extensive experiments validate that our method has advantages in matching structured non-planar scenes under large viewpoint changes and illumination variations.