Abstract

The image-to-GPS verification problem asks whether a given image is taken at a claimed GPS location. In this paper, we treat it as an image verification problem – whether a query image is taken at the same place as a reference image retrieved at the claimed GPS location. We make three major contributions: (1) we propose a novel custom bottom-up pattern matching (BUPM) deep neural network solution; (2) we demonstrate that the verification can be directly done by cross-checking a perspective-looking query image and a panorama reference image, and (3) we collect and clean a dataset of 30K pairs query and reference. Our experimental results show that the proposed BUPM solution outperforms the state-of-the-art solutions in terms of both verification and localization.

Date

2019

Authors

Jiaxin Cheng, Yue Wu, Wael Abd-Almageed, Prem Natarajan

Conference

Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers, Part V 14

Pages

546-561

Publisher

Springer International Publishing