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LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS
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| Zeitschriftentitel: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
|---|---|
| Personen und Körperschaften: | , , , |
| In: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2/W5, 2019, S. 13-20 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Copernicus GmbH
|
| Schlagwörter: |
| author_facet |
Chen, M. Zhu, Q. Yan, S. Zhao, Y. Chen, M. Zhu, Q. Yan, S. Zhao, Y. |
|---|---|
| author |
Chen, M. Zhu, Q. Yan, S. Zhao, Y. |
| spellingShingle |
Chen, M. Zhu, Q. Yan, S. Zhao, Y. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS General Medicine |
| author_sort |
chen, m. |
| spelling |
Chen, M. Zhu, Q. Yan, S. Zhao, Y. 2194-9050 Copernicus GmbH General Medicine http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-13-2019 <jats:p>Abstract. Feature matching is a fundamental technical issue in many applications of photogrammetry and remote sensing. Although recently developed local feature detectors and descriptors have contributed to the advancement of point matching, challenges remain with regard to urban area images that are characterized by large discrepancies in viewing angles. In this paper, we define a concept of local geometrical structure (LGS) and propose a novel feature matching method by exploring the LGS of interest points to specifically address difficult situations in matching points on wide-baseline urban area images. In this study, we first detect interest points from images using a popular detector and compute the LGS of each interest point. Then, the interest points are classified into three categories on the basis of LGS. Thereafter, a hierarchical matching framework that is robust to image viewpoint change is proposed to compute correspondences, in which different feature region computation methods, description methods, and matching strategies are designed for various types of interest points according to their LGS properties. Finally, random sample consensus algorithm based on fundamental matrix is applied to eliminate outliers. The proposed method can generate similar feature descriptors for corresponding interest points under large viewpoint variation even in discontinuous areas that benefit from the LGS-based adaptive feature region construction. Experimental results demonstrate that the proposed method provides significant improvements in correct match number and matching precision compared with other traditional matching methods for urban area wide-baseline images. </jats:p> LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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10.5194/isprs-annals-iv-2-w5-13-2019 |
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Online |
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ElectronicArticle |
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DE-Gla1 DE-Zi4 DE-15 DE-Pl11 DE-Rs1 DE-105 DE-14 DE-Ch1 DE-L229 DE-D275 DE-Bn3 DE-Brt1 DE-Zwi2 DE-D161 |
| imprint |
Copernicus GmbH, 2019 |
| imprint_str_mv |
Copernicus GmbH, 2019 |
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2194-9050 |
| issn_str_mv |
2194-9050 |
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English |
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chen2019lgslocalgeometricalstructurebasedinterestpointmatchingforwidebaselineimageryinurbanareas |
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2019 |
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Copernicus GmbH |
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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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49 |
| title |
LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_unstemmed |
LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_full |
LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_fullStr |
LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_full_unstemmed |
LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_short |
LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_sort |
lgs: local geometrical structure-based interest point matching for wide-baseline imagery in urban areas |
| topic |
General Medicine |
| url |
http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-13-2019 |
| publishDate |
2019 |
| physical |
13-20 |
| description |
<jats:p>Abstract. Feature matching is a fundamental technical issue in many applications of photogrammetry and remote sensing. Although recently developed local feature detectors and descriptors have contributed to the advancement of point matching, challenges remain with regard to urban area images that are characterized by large discrepancies in viewing angles. In this paper, we define a concept of local geometrical structure (LGS) and propose a novel feature matching method by exploring the LGS of interest points to specifically address difficult situations in matching points on wide-baseline urban area images. In this study, we first detect interest points from images using a popular detector and compute the LGS of each interest point. Then, the interest points are classified into three categories on the basis of LGS. Thereafter, a hierarchical matching framework that is robust to image viewpoint change is proposed to compute correspondences, in which different feature region computation methods, description methods, and matching strategies are designed for various types of interest points according to their LGS properties. Finally, random sample consensus algorithm based on fundamental matrix is applied to eliminate outliers. The proposed method can generate similar feature descriptors for corresponding interest points under large viewpoint variation even in discontinuous areas that benefit from the LGS-based adaptive feature region construction. Experimental results demonstrate that the proposed method provides significant improvements in correct match number and matching precision compared with other traditional matching methods for urban area wide-baseline images.
</jats:p> |
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| author | Chen, M., Zhu, Q., Yan, S., Zhao, Y. |
| author_facet | Chen, M., Zhu, Q., Yan, S., Zhao, Y., Chen, M., Zhu, Q., Yan, S., Zhao, Y. |
| author_sort | chen, m. |
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| container_title | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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| description | <jats:p>Abstract. Feature matching is a fundamental technical issue in many applications of photogrammetry and remote sensing. Although recently developed local feature detectors and descriptors have contributed to the advancement of point matching, challenges remain with regard to urban area images that are characterized by large discrepancies in viewing angles. In this paper, we define a concept of local geometrical structure (LGS) and propose a novel feature matching method by exploring the LGS of interest points to specifically address difficult situations in matching points on wide-baseline urban area images. In this study, we first detect interest points from images using a popular detector and compute the LGS of each interest point. Then, the interest points are classified into three categories on the basis of LGS. Thereafter, a hierarchical matching framework that is robust to image viewpoint change is proposed to compute correspondences, in which different feature region computation methods, description methods, and matching strategies are designed for various types of interest points according to their LGS properties. Finally, random sample consensus algorithm based on fundamental matrix is applied to eliminate outliers. The proposed method can generate similar feature descriptors for corresponding interest points under large viewpoint variation even in discontinuous areas that benefit from the LGS-based adaptive feature region construction. Experimental results demonstrate that the proposed method provides significant improvements in correct match number and matching precision compared with other traditional matching methods for urban area wide-baseline images. </jats:p> |
| doi_str_mv | 10.5194/isprs-annals-iv-2-w5-13-2019 |
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| imprint | Copernicus GmbH, 2019 |
| imprint_str_mv | Copernicus GmbH, 2019 |
| institution | DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161 |
| issn | 2194-9050 |
| issn_str_mv | 2194-9050 |
| language | English |
| last_indexed | 2024-03-01T15:51:11.878Z |
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| physical | 13-20 |
| publishDate | 2019 |
| publishDateSort | 2019 |
| publisher | Copernicus GmbH |
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| series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| source_id | 49 |
| spelling | Chen, M. Zhu, Q. Yan, S. Zhao, Y. 2194-9050 Copernicus GmbH General Medicine http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-13-2019 <jats:p>Abstract. Feature matching is a fundamental technical issue in many applications of photogrammetry and remote sensing. Although recently developed local feature detectors and descriptors have contributed to the advancement of point matching, challenges remain with regard to urban area images that are characterized by large discrepancies in viewing angles. In this paper, we define a concept of local geometrical structure (LGS) and propose a novel feature matching method by exploring the LGS of interest points to specifically address difficult situations in matching points on wide-baseline urban area images. In this study, we first detect interest points from images using a popular detector and compute the LGS of each interest point. Then, the interest points are classified into three categories on the basis of LGS. Thereafter, a hierarchical matching framework that is robust to image viewpoint change is proposed to compute correspondences, in which different feature region computation methods, description methods, and matching strategies are designed for various types of interest points according to their LGS properties. Finally, random sample consensus algorithm based on fundamental matrix is applied to eliminate outliers. The proposed method can generate similar feature descriptors for corresponding interest points under large viewpoint variation even in discontinuous areas that benefit from the LGS-based adaptive feature region construction. Experimental results demonstrate that the proposed method provides significant improvements in correct match number and matching precision compared with other traditional matching methods for urban area wide-baseline images. </jats:p> LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spellingShingle | Chen, M., Zhu, Q., Yan, S., Zhao, Y., ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS, General Medicine |
| title | LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_full | LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_fullStr | LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_full_unstemmed | LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_short | LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| title_sort | lgs: local geometrical structure-based interest point matching for wide-baseline imagery in urban areas |
| title_unstemmed | LGS: LOCAL GEOMETRICAL STRUCTURE-BASED INTEREST POINT MATCHING FOR WIDE-BASELINE IMAGERY IN URBAN AREAS |
| topic | General Medicine |
| url | http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-13-2019 |