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Journal of SensorsVolume 2013 2013, Article ID 843727, 9 pages

Research Article

School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

School of Optoelectronics, Beijing Institute of Technology, Beijing, China

Received 31 May 2013; Revised 23 September 2013; Accepted 28 September 2013

Academic Editor: Eugenio Martinelli

Copyright © 2013 Zhenwen Gui et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper addresses the recognition of large-scale outdoor scenes on smartphones by fusing outputs of inertial sensors and computer vision techniques. The main contributions can be summarized as follows. Firstly, we propose an ORD overlap region divide method to plot image position area, which is fast enough to find the nearest visiting area and can also reduce the search range compared with the traditional approaches. Secondly, the vocabulary tree-based approach is improved by introducing GAGCC gravity-aligned geometric consistency constraint. Our method involves no operation in the high-dimensional feature space and does not assume a global transform between a pair of images. Thus, it substantially reduces the computational complexity and memory usage, which makes the city scale image recognition feasible on the smartphone. Experiments on a collected database including 0.16 million images show that the proposed method demonstrates excellent recognition performance, while maintaining the average recognition time about 1 s.

Author: Zhenwen Gui, Yongtian Wang, Yue Liu, and Jing Chen



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