{"title":"加入街景图像和建筑足迹GIS数据","authors":"Y. Ogawa, Takuya Oki, Shenglong Chen, Y. Sekimoto","doi":"10.1145/3486640.3491395","DOIUrl":null,"url":null,"abstract":"This paper proposes a new method to join building footprint GIS data with the relevant buildings in a street-view image, taken by a vehicle-mounted camera. This is achieved by segmenting buildings in the street-view images and identifying the relevant building coordinates in the image. The building coordinates on the image are then estimated from the building vertices in the building footprint GIS data and vehicle trajectory history. Finally, the objective building is identified and relevant building attributes corresponding to each building image are linked together. This method enables the development of building image datasets with associated building attributes. The building image data, when linked to the relevant building attributes, could contribute to many innovative urban analyses, such as urban monitoring, the development of three-dimensional (3D) city models, and image datasets for training with annotated building attributes.","PeriodicalId":315583,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Joining Street-View Images and Building Footprint GIS Data\",\"authors\":\"Y. Ogawa, Takuya Oki, Shenglong Chen, Y. Sekimoto\",\"doi\":\"10.1145/3486640.3491395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a new method to join building footprint GIS data with the relevant buildings in a street-view image, taken by a vehicle-mounted camera. This is achieved by segmenting buildings in the street-view images and identifying the relevant building coordinates in the image. The building coordinates on the image are then estimated from the building vertices in the building footprint GIS data and vehicle trajectory history. Finally, the objective building is identified and relevant building attributes corresponding to each building image are linked together. This method enables the development of building image datasets with associated building attributes. The building image data, when linked to the relevant building attributes, could contribute to many innovative urban analyses, such as urban monitoring, the development of three-dimensional (3D) city models, and image datasets for training with annotated building attributes.\",\"PeriodicalId\":315583,\"journal\":{\"name\":\"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3486640.3491395\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3486640.3491395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Joining Street-View Images and Building Footprint GIS Data
This paper proposes a new method to join building footprint GIS data with the relevant buildings in a street-view image, taken by a vehicle-mounted camera. This is achieved by segmenting buildings in the street-view images and identifying the relevant building coordinates in the image. The building coordinates on the image are then estimated from the building vertices in the building footprint GIS data and vehicle trajectory history. Finally, the objective building is identified and relevant building attributes corresponding to each building image are linked together. This method enables the development of building image datasets with associated building attributes. The building image data, when linked to the relevant building attributes, could contribute to many innovative urban analyses, such as urban monitoring, the development of three-dimensional (3D) city models, and image datasets for training with annotated building attributes.