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Robust Feature Correspondences from a Large Set of Unsorted Wide Baseline Images
Cao, Yanpeng; McDonald, John
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.
Keyword(s): Computer Science; feature correspondence; wide baseline matching; image self-organization; computer vision; image matching
Publication Date:
Type: Journal article
Peer-Reviewed: Yes
Institution: Maynooth University
Funder(s): Science Foundation Ireland
Citation(s): 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
Publisher(s): IEEE
File Format(s): application/pdf
Related Link(s):
First Indexed: 2020-01-31 06:00:05 Last Updated: 2020-04-02 07:36:28