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.
CITATION STYLE
Çelik, N., & Sümer, E. (2020). Geo-tagged image retrieval from mapillary street images for a target building. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 44, pp. 151–158). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-151-2020
Mendeley helps you to discover research relevant for your work.