WACV 2015: IEEE Winter Conference on Applications of Computer Vision
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Predicting where a photo was taken is quite important and yet a challenging task for computer vision algorithms. Our motivation is to solve this difficult problem in a city-scale setting by employing a data-driven approach. In order to pursue this goal, we developed a fast and robust scene matching method that follows a coarse-to-fine strategy. In particular, we combine scene retrieval via global features and dense scene alignment and use a large set of geo-tagged images of downtown San Francisco in our evaluation. The experimental results show that the proposed approach, despite its simplicity, is surprisingly effective and achieves comparable results with the state-of-the-art.
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S. Yagcioglu, E. Erdem, A. Erdem. City Scale Image Geolocalization via Dense Scene Alignment. The WACV 2015: IEEE Winter Conference on Applications of Computer Vision, Hawaii, USA, January 2015
@inproceedings{yagcioglu2015city,
author = {Yagcioglu, Semih and Erdem, Erkut and Erdem, Aykut},
title = {City Scale Image Geolocalization via Dense Scene Alignment},
booktitle = {Applications of Computer Vision (WACV), 2015 IEEE Winter Conference on},
year = {2015},
organization = {IEEE}}
For comments and questions, please contact Semih Yagcioglu.
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