City Scale Image Geolocalization via Dense Scene Alignment

Yagcioglu S., ERDEM M. E., Erdem A.

IEEE Winter Conference on Applications of Computer Vision (WACV 2015), Hawaii, United States Of America, 6 - 09 January 2015, pp.726-732 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/wacv.2015.102
  • City: Hawaii
  • Country: United States Of America
  • Page Numbers: pp.726-732
  • Hacettepe University Affiliated: Yes

Abstract

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.