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首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >GEO-TAGGED IMAGE RETRIEVAL FROM MAPILLARY STREET IMAGES FOR A TARGET BUILDING
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GEO-TAGGED IMAGE RETRIEVAL FROM MAPILLARY STREET IMAGES FOR A TARGET BUILDING

机译:来自马地图族的街道图像的地理标记的图像检索,用于目标建筑物

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This study aims to investigate the possibility to automate the image selection process for the target building from Mapillary images through a web application where the user only initiates one image of the target building as a query. Using the data provided with Mapillary API and Overpass API, all images having full or partial coverage of the target building were selected. Then the images were segmented by using a pre-trained U-Net model to discard any images having less than 20% building coverage. The experiments showed promising results yielding 0.971 and 0.887 of overall accuracy after segmentation steps for two different target buildings.
机译:本研究旨在通过Web应用程序调查从Mapillary图像自动执行目标建筑物的图像选择过程,其中用户仅将目标建筑物的一个图像作为查询启动。使用具有Mapillary API和OverApase API的数据,选择了具有全部或部分覆盖目标建筑物的所有图像。然后通过使用预先训练的U-Net模型进行图像进行分段,以丢弃具有少于20%的建筑覆盖率的任何图像。实验表明,两种不同靶建筑物后,在分割步骤后的总精度的总精度为0.971和0.887。

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