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MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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IEEE Transactions on Knowledge and Data Engineering
Detecting dominant locations from search queries
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Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
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WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Peekaboom: a game for locating objects in images
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The Design of High-Level Features for Photo Quality Assessment
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
AnnoSearch: Image Auto-Annotation by Search
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Computer
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Image Based Localization in Urban Environments
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
The dogear game: a social bookmark recommender system
Proceedings of the 2007 international ACM conference on Supporting group work
Hierarchical photo organization using geo-relevance
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Pagerank for product image search
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A crowdsourcing based mobile image translation and knowledge sharing service
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Guess who?: enriching the social graph through a crowdsourcing game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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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.