A robust method for recovering geometric proxy from multiple panoramic images
The use of multiple panoramic images for walkthrough applications is attracting more attention in recent years. The geometric proxy, which can be recovered from wide-baseline images can be used to reduce the sampling rate. However correspondence matching across widely separated panoramic images requ...
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sg-smu-ink.sis_research-76892022-01-13T05:30:03Z A robust method for recovering geometric proxy from multiple panoramic images WAN, Ada S. K. SIU, Angus M. K. LAU, Rynson W. H. NGO, Chong-wah The use of multiple panoramic images for walkthrough applications is attracting more attention in recent years. The geometric proxy, which can be recovered from wide-baseline images can be used to reduce the sampling rate. However correspondence matching across widely separated panoramic images requires searching a large disparity range, which can significantly increase the number of false matches. In addition, 3D point estimation along the antipodal direction of panoramic images is unreliable due to small vergence angle. Moreover, existing methods only recover 3D points, which do not provide information about object continuity in the scene. In this paper, we propose a robust method for recovering geometric proxy of a scene from multiple wide-baseline panoramic images. Correspondences are matched under the epipolar constraint. A robust algorithm is developed to remove false matches and estimate a set of reliable sparse 3D points. We further recover information about object continuity with topology and pattern similarity checking. 2004-10-27T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/6686 info:doi/10.1109/ICIP.2004.1419756 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Graphics and Human Computer Interfaces |
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Computer Sciences Graphics and Human Computer Interfaces WAN, Ada S. K. SIU, Angus M. K. LAU, Rynson W. H. NGO, Chong-wah A robust method for recovering geometric proxy from multiple panoramic images |
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The use of multiple panoramic images for walkthrough applications is attracting more attention in recent years. The geometric proxy, which can be recovered from wide-baseline images can be used to reduce the sampling rate. However correspondence matching across widely separated panoramic images requires searching a large disparity range, which can significantly increase the number of false matches. In addition, 3D point estimation along the antipodal direction of panoramic images is unreliable due to small vergence angle. Moreover, existing methods only recover 3D points, which do not provide information about object continuity in the scene. In this paper, we propose a robust method for recovering geometric proxy of a scene from multiple wide-baseline panoramic images. Correspondences are matched under the epipolar constraint. A robust algorithm is developed to remove false matches and estimate a set of reliable sparse 3D points. We further recover information about object continuity with topology and pattern similarity checking. |
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text |
author |
WAN, Ada S. K. SIU, Angus M. K. LAU, Rynson W. H. NGO, Chong-wah |
author_facet |
WAN, Ada S. K. SIU, Angus M. K. LAU, Rynson W. H. NGO, Chong-wah |
author_sort |
WAN, Ada S. K. |
title |
A robust method for recovering geometric proxy from multiple panoramic images |
title_short |
A robust method for recovering geometric proxy from multiple panoramic images |
title_full |
A robust method for recovering geometric proxy from multiple panoramic images |
title_fullStr |
A robust method for recovering geometric proxy from multiple panoramic images |
title_full_unstemmed |
A robust method for recovering geometric proxy from multiple panoramic images |
title_sort |
robust method for recovering geometric proxy from multiple panoramic images |
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Institutional Knowledge at Singapore Management University |
publishDate |
2004 |
url |
https://ink.library.smu.edu.sg/sis_research/6686 |
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