Finding the correspondence points in images of multi-views
There are many approaches being proposed to find the correspondence points between two images. They generally perform when used to find the correspondences between two images of the same object, such as in a video sequence or in a stereo camera. However, they fail if the number of true matches betwe...
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sg-ntu-dr.10356-799042020-03-07T13:24:43Z Finding the correspondence points in images of multi-views Yau, Wei-Yun Teoh, Eam Khwang Anvar, Seyed Mohammad Hassan School of Electrical and Electronic Engineering International Conference on Signal-Image Technology & Internet-Based Systems (8th : 2012 : Naples, Italy) There are many approaches being proposed to find the correspondence points between two images. They generally perform when used to find the correspondences between two images of the same object, such as in a video sequence or in a stereo camera. However, they fail if the number of true matches between two images was small compared to all the potential correspondence points found, which could happen if both scenes vary significantly, such as when the objects are not the same but of the same class. In this paper, we proposed an approach which uses both the geometric and appearance features to find the true correspondence points even if the number of true matches was small portion compared to all the correspondence points found. The experimental results show that the proposed method also stabilizes very fast compared to the other approaches in the literature. Accepted version 2013-07-25T06:41:15Z 2019-12-06T13:36:27Z 2013-07-25T06:41:15Z 2019-12-06T13:36:27Z 2012 2012 Conference Paper Anvar, S. M. H., Yau, W.-Y., & Teoh, E. K. (2012). Finding the Correspondence Points in Images of Multi-Views. 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems (SITIS), 275-280. https://hdl.handle.net/10356/79904 http://hdl.handle.net/10220/12248 10.1109/SITIS.2012.48 en © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/SITIS.2012.48]. application/pdf |
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There are many approaches being proposed to find the correspondence points between two images. They generally perform when used to find the correspondences between two images of the same object, such as in a video sequence or in a stereo camera. However, they fail if the number of true matches between two images was small compared to all the potential correspondence points found, which could happen if both scenes vary significantly, such as when the objects are not the same but of the same class. In this paper, we proposed an approach which uses both the geometric and appearance features to find the true correspondence points even if the number of true matches was small portion compared to all the correspondence points found. The experimental results show that the proposed method also stabilizes very fast compared to the other approaches in the literature. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Yau, Wei-Yun Teoh, Eam Khwang Anvar, Seyed Mohammad Hassan |
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Conference or Workshop Item |
author |
Yau, Wei-Yun Teoh, Eam Khwang Anvar, Seyed Mohammad Hassan |
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Yau, Wei-Yun Teoh, Eam Khwang Anvar, Seyed Mohammad Hassan Finding the correspondence points in images of multi-views |
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Yau, Wei-Yun |
title |
Finding the correspondence points in images of multi-views |
title_short |
Finding the correspondence points in images of multi-views |
title_full |
Finding the correspondence points in images of multi-views |
title_fullStr |
Finding the correspondence points in images of multi-views |
title_full_unstemmed |
Finding the correspondence points in images of multi-views |
title_sort |
finding the correspondence points in images of multi-views |
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2013 |
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https://hdl.handle.net/10356/79904 http://hdl.handle.net/10220/12248 |
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