AN AUTOMATIC SEMANTIC MAP GENERATION METHOD USING TRAJECTORY DATA
It’s easily to obtain the geometric information of terrain features in a timely manner using advanced surveying and mapping methods, but it is impossible to obtain their semantic information with low latency due to the rapid development of cities. The popularity of GPS-enabled devices and technologi...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-08-01
|
| 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/XLIII-B4-2020/63/2020/isprs-archives-XLIII-B4-2020-63-2020.pdf |
| _version_ | 1818478166345252864 |
|---|---|
| author | Y. Miao X. Tang Z. Wang |
| author_facet | Y. Miao X. Tang Z. Wang |
| author_sort | Y. Miao |
| collection | DOAJ |
| description | It’s easily to obtain the geometric information of terrain features in a timely manner using advanced surveying and mapping methods, but it is impossible to obtain their semantic information with low latency due to the rapid development of cities. The popularity of GPS-enabled devices and technologies provide us a large number of personal location information. Moreover, it is possible to extract the personal or group behavior pattern due to the regularity of human behavior. Those conditions make it possible to extract and identify human behavior patterns from their trajectory data. In this paper, we present an automatic semantic map generation method that extract semantic patterns and take advantage of them to tagging spatial objects in an unknown region based on known semantic patterns. We study the regularity of trajectory data and build the semantic pattern based on the regularity of human behavior. Most importantly, we use known semantic patterns to identify the semantics of the stay points in the unknown region, and use this method to realize the semantic recognition of the stay points. Results of the experiments show the effectiveness of our proposed method. |
| first_indexed | 2024-12-10T09:44:56Z |
| format | Article |
| id | doaj.art-c336f66243fd466994a2f1ab810d93e1 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-10T09:44:56Z |
| publishDate | 2020-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-c336f66243fd466994a2f1ab810d93e12022-12-22T01:53:52ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B4-2020636710.5194/isprs-archives-XLIII-B4-2020-63-2020AN AUTOMATIC SEMANTIC MAP GENERATION METHOD USING TRAJECTORY DATAY. Miao0X. Tang1Z. Wang2School of Computer Science, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Computer Science, Wuhan University, Wuhan, ChinaIt’s easily to obtain the geometric information of terrain features in a timely manner using advanced surveying and mapping methods, but it is impossible to obtain their semantic information with low latency due to the rapid development of cities. The popularity of GPS-enabled devices and technologies provide us a large number of personal location information. Moreover, it is possible to extract the personal or group behavior pattern due to the regularity of human behavior. Those conditions make it possible to extract and identify human behavior patterns from their trajectory data. In this paper, we present an automatic semantic map generation method that extract semantic patterns and take advantage of them to tagging spatial objects in an unknown region based on known semantic patterns. We study the regularity of trajectory data and build the semantic pattern based on the regularity of human behavior. Most importantly, we use known semantic patterns to identify the semantics of the stay points in the unknown region, and use this method to realize the semantic recognition of the stay points. Results of the experiments show the effectiveness of our proposed method.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B4-2020/63/2020/isprs-archives-XLIII-B4-2020-63-2020.pdf |
| spellingShingle | Y. Miao X. Tang Z. Wang AN AUTOMATIC SEMANTIC MAP GENERATION METHOD USING TRAJECTORY DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | AN AUTOMATIC SEMANTIC MAP GENERATION METHOD USING TRAJECTORY DATA |
| title_full | AN AUTOMATIC SEMANTIC MAP GENERATION METHOD USING TRAJECTORY DATA |
| title_fullStr | AN AUTOMATIC SEMANTIC MAP GENERATION METHOD USING TRAJECTORY DATA |
| title_full_unstemmed | AN AUTOMATIC SEMANTIC MAP GENERATION METHOD USING TRAJECTORY DATA |
| title_short | AN AUTOMATIC SEMANTIC MAP GENERATION METHOD USING TRAJECTORY DATA |
| title_sort | automatic semantic map generation method using trajectory data |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B4-2020/63/2020/isprs-archives-XLIII-B4-2020-63-2020.pdf |
| work_keys_str_mv | AT ymiao anautomaticsemanticmapgenerationmethodusingtrajectorydata AT xtang anautomaticsemanticmapgenerationmethodusingtrajectorydata AT zwang anautomaticsemanticmapgenerationmethodusingtrajectorydata AT ymiao automaticsemanticmapgenerationmethodusingtrajectorydata AT xtang automaticsemanticmapgenerationmethodusingtrajectorydata AT zwang automaticsemanticmapgenerationmethodusingtrajectorydata |