Cao, Yanpeng and McDonald, John (2009) Robust Feature Correspondences from a Large Set of Unsorted Wide Baseline Images. Image Processing (ICIP), 2009 16th IEEE International Conference on . 4277 -4280. ISSN 1522-4880
Download (1MB)
|
Abstract
Given a set of unordered images taken in a wide area, an effective solution is proposed for establishing robust feature correspondences among them. Two major improvements are made in our work as follows: firstly, a robust technique is proposed for the self-organization of a large number of images without spatial orderings; secondly, a novel wide-baseline matching approach is developed to obtain good correspondences over images taken from substantially different viewpoints. The output consists of many sets of reliable pair-wise feature correspondences which are essential in various computer vision applications. Realistic experiments were carried out to evaluate the performances of the proposed method by using a large amount of images captured from our university’s campus.
Item Type: | Article |
---|---|
Additional Information: | Research presented in this paper was funded by a Strategic Research Cluster grant (07/SRC/I1168) by Science Foundation Ireland under the National Development Plan. |
Keywords: | feature correspondence; wide baseline matching; image self-organization; computer vision; image matching; |
Academic Unit: | Faculty of Science and Engineering > Computer Science |
Item ID: | 2326 |
Identification Number: | https://doi.org/10.1109/ICIP.2009.5413689 |
Depositing User: | John McDonald |
Date Deposited: | 11 Jan 2011 16:58 |
Journal or Publication Title: | Image Processing (ICIP), 2009 16th IEEE International Conference on |
Publisher: | IEEE |
Refereed: | Yes |
Funders: | Science Foundation Ireland |
URI: | |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only(login required)
Item control page |
Downloads
Downloads per month over past year