HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW
Maintaining an up-to-date inventory of urban infrastructure such as fire hydrant is critical to urban management. Street view database such as Google Street View and Baidu Street View contain street-level images, their potential for urban management has not been fully explored. For the massive image...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1295/2019/isprs-archives-XLII-2-W13-1295-2019.pdf |
| _version_ | 1818613158645858304 |
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| author | M. Du J. Wang C. Jing J. Jiang Q. Chen |
| author_facet | M. Du J. Wang C. Jing J. Jiang Q. Chen |
| author_sort | M. Du |
| collection | DOAJ |
| description | Maintaining an up-to-date inventory of urban infrastructure such as fire hydrant is critical to urban management. Street view database such as Google Street View and Baidu Street View contain street-level images, their potential for urban management has not been fully explored. For the massive image, data model for storage and indexing is an important research issue. Considering multiple cameras and GPS device in the image capturing platform, a hierarchical data model named 3D-Grid is proposed. Massive street view images were stored according to grid ID, GPS time and camera ID. An efficient time indexing algorithm is brought forth to replace the spatial indexing. Real test experiments are conducted in a project, and the validation and feasibility of 3D-Grid including time indexing algorithm were validated. |
| first_indexed | 2024-12-16T15:57:40Z |
| format | Article |
| id | doaj.art-e14a2cd67ae14c5b832f8ec06d101bf3 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-16T15:57:40Z |
| publishDate | 2019-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-e14a2cd67ae14c5b832f8ec06d101bf32022-12-21T22:25:32ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342019-06-01XLII-2-W131295129910.5194/isprs-archives-XLII-2-W13-1295-2019HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEWM. Du0J. Wang1C. Jing2J. Jiang3Q. Chen4School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, ChinaSchool of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, ChinaSchool of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, ChinaSchool of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, ChinaSchool of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, ChinaMaintaining an up-to-date inventory of urban infrastructure such as fire hydrant is critical to urban management. Street view database such as Google Street View and Baidu Street View contain street-level images, their potential for urban management has not been fully explored. For the massive image, data model for storage and indexing is an important research issue. Considering multiple cameras and GPS device in the image capturing platform, a hierarchical data model named 3D-Grid is proposed. Massive street view images were stored according to grid ID, GPS time and camera ID. An efficient time indexing algorithm is brought forth to replace the spatial indexing. Real test experiments are conducted in a project, and the validation and feasibility of 3D-Grid including time indexing algorithm were validated.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1295/2019/isprs-archives-XLII-2-W13-1295-2019.pdf |
| spellingShingle | M. Du J. Wang C. Jing J. Jiang Q. Chen HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW |
| title_full | HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW |
| title_fullStr | HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW |
| title_full_unstemmed | HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW |
| title_short | HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW |
| title_sort | hierarchical data model for storage and indexing of massive street view |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1295/2019/isprs-archives-XLII-2-W13-1295-2019.pdf |
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