Quasi-Dense Matching between Perspective and Omnidirectional Images
Year: 2008
Type: article
Abstract: . In this paper, we propose a match propagation algorithm between perspective and omnidirectional images of same scene consisting of planes, which does not require a rectification for the omnidirectional image. First, a linear transformation is introduced to identify the area containing the corresponding point candidates. Then, a geometric invariant is computed as a constraint for quasi-dense matching. Finally, combining the computed geometric invariant with a best-first strategy of Lhuillier and Quan (2002), the quasi-dense point correspondences are calculated. The experiments with real data show that the algorithm of this paper has good performance. 1
Authors: Lingling Lu, Yihong Wu
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2965950732