Region-based landmark discovery by crowdsourcing geo-referenced photos

Authors:
Yen-Ta Huang;An-Jung Cheng;Liang-Chi Hsieh;Winston Hsu;Kuo-Wei Chang
Affiliations:
National Taiwan University, Taipei, Taiwan Roc;National Taiwan University, Taipei, Taiwan Roc;National Taiwan University, Taipei, Taiwan Roc;National Taiwan University, Taipei, Taiwan Roc;Chunghwa Telecom Co., Ltd.,, Taipei, Taiwan Roc
Venue:
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Year:
2011

Citing 2
Cited 0

Mapping the world's photos

Proceedings of the 18th international conference on World wide web
Social pixels: genesis and evaluation

Proceedings of the international conference on Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a novel model for landmark discovery that locates region-based landmarks on map in contrast to the traditional point-based landmarks. The proposed method preserves more information and automatically identifies candidate regions on map by crowdsourcing geo-referenced photos. Gaussian kernel convolution is applied to remove noises and generate detected region. We adopt F1 measure to evaluate discovered landmarks and manually check the association between tags and regions. The experiment results show that more than 90% of attractions in the selected city can be correctly located by this method.