Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6938801 | Pattern Recognition | 2018 | 13 Pages |
Abstract
Line matching across views is a fundamental task in many applications. Existing methods are hardly applicable to across view scenarios due to the limitation of line descriptors and matching strategy. In this paper, we present a novel line-points invariant based on a new projective invariant named characteristic number. The invariant is able to reflect the intrinsic geometry of line and points, which keeps invariant across views. The construction of this invariant uses intersections of coplanar lines instead of endpoints, rendering more robust matching across views. Accurate homography recovered from the invariant allows all lines, even those without interest points around them, a chance to be matched. Extensive comparisons with the state-of-the-art validate the matching accuracy and robustness of the proposed method to projective transformations. The method also performs well for image pairs with similar textures and those of low textures.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Qi Jia, Xin Fan, Xinkai Gao, Meiyu Yu, Haojie Li, Zhongxuan Luo,