Object Geolocation from Crowdsourced Street Level Imagery. Krylov, V. A. & Dahyot, R. In Alzate, C., Monreale, A., Assem, H., Bifet, A., Buda, T. S., Caglayan, B., Drury, B., García-Martín, Eva, Gavaldà, R., Kramer, S., Lavesson, N., Madden, M., Molloy, I., Nicolae, M., & Sinn, M., editors, ECML PKDD 2018 Workshops, pages 79–83, Cham, 2019. Springer International Publishing.
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Paper doi abstract bibtex 1 download
Paper doi abstract bibtex 1 download We explore the applicability and limitations of a state-of-the-art object detection and geotagging system [4] applied to crowdsourced image data. Our experiments with imagery from Mapillary crowdsourcing platform demonstrate that with increasing amount of images, the detection accuracy is getting close to that obtained with high-end street level data. Nevertheless, due to excessive camera position noise, the estimated geolocation (position) of the detected object is less accurate on crowdsourced Mapillary imagery than with high-end street level imagery obtained by Google Street View.
@InProceedings{10.1007/978-3-030-13453-2_7,
author = {Krylov, Vladimir A. and Dahyot, Rozenn},
editor = {Alzate, Carlos
and Monreale, Anna
and Assem, Haytham
and Bifet, Albert
and Buda, Teodora Sandra
and Caglayan, Bora
and Drury, Brett
and Garc{\'i}a-Mart{\'i}n, Eva
and Gavald{\`a}, Ricard
and Kramer, Stefan
and Lavesson, Niklas
and Madden, Michael
and Molloy, Ian
and Nicolae, Maria-Irina
and Sinn, Mathieu},
doi = {10.1007/978-3-030-13453-2_7},
url = {https://mural.maynoothuniversity.ie/15249/1/RD_object.pdf},
title = {Object Geolocation from Crowdsourced Street Level Imagery},
booktitle = {ECML PKDD 2018 Workshops},
year = {2019},
publisher = {Springer International Publishing},
address = {Cham},
pages = {79--83},
abstract = {We explore the applicability and limitations of a state-of-the-art object
detection and geotagging system [4] applied to crowdsourced image data. Our experiments with
imagery from Mapillary crowdsourcing platform demonstrate that with increasing amount of images,
the detection accuracy is getting close to that obtained with high-end street level data. Nevertheless,
due to excessive camera position noise, the estimated geolocation (position) of the detected object is
less accurate on crowdsourced Mapillary imagery than with high-end street level imagery obtained by Google Street View.},
isbn = {978-3-030-13453-2}}Downloads: 1
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