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A game based approach to assign geographical relevance to web images
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International World Wide Web Conference archive
Proceedings of the 18th international conference on World wide web table of contents
Madrid, Spain
SESSION: User interfaces and mobile web/session: mobile web table of contents
Pages 811-820  
Year of Publication: 2009
ISBN:978-1-60558-487-4
Authors
Yuki Arase  Osaka University, Osaka, Japan
Xing Xie  Microsoft Research Asia, Beijing, China
Manni Duan  University of Science and Technology of China, Hefei, China
Takahiro Hara  Osaka University, Osaka, Japan
Shojiro Nishio  Osaka University, Osaka, Japan
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Geographical context is very important for images. Millions of images on the Web have been already assigned latitude and longitude information. Due to the rapid proliferation of such images with geographical context, it is still difficult to effectively search and browse them, since we do not have ways to decide their relevance. In this paper, we focus on the geographical relevance of images, which is defined as to what extent the main objects in an image match landmarks at the location where the image was taken. Recently, researchers have proposed to use game based approaches to label large scale data such as Web images. However, previous works have not shown the quality of collected game logs in detail and how the logs can improve existing applications. To answer these questions, we design and implement a Web-based and multi-player game to collect human knowledge while people are enjoying the game. Then we thoroughly analyze the game logs obtained during a three week study with 147 participants and propose methods to determine the image geographical relevance. In addition, we conduct an experiment to compare our methods with a commercial search engine. Experimental results show that our methods dramatically improve image search relevance. Furthermore, we show that we can derive geographically relevant objects and their salient portion in images, which is valuable for a number of applications such as image location recognition.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Yuki Arase: colleagues
Xing Xie: colleagues
Manni Duan: colleagues
Takahiro Hara: colleagues
Shojiro Nishio: colleagues