从目标建筑物的主街图像中检索地理标记图像

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Pub Date : 2020-11-23 DOI:10.5194/isprs-archives-xliv-4-w3-2020-151-2020

N. Celik, E. Sümer

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引用次数: 2

摘要

摘要本研究旨在探讨通过web应用程序从Mapillary图像中自动选择目标建筑物图像的可能性，其中用户仅启动目标建筑物的一张图像作为查询。使用Mapillary API和Overpass API提供的数据，选择所有完全或部分覆盖目标建筑物的图像。然后，使用预训练的U-Net模型对图像进行分割，去除建筑物覆盖率低于20%的图像。实验结果表明，对两种不同的目标建筑进行分割后，总体准确率分别为0.971和0.887。

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GEO-TAGGED IMAGE RETRIEVAL FROM MAPILLARY STREET IMAGES FOR A TARGET BUILDING

Abstract. 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.

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ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

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