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A game based approach to assign geographical relevance to web images

Published: 20 April 2009 Publication History

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.

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  1. A game based approach to assign geographical relevance to web images

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    cover image ACM Conferences
    WWW '09: Proceedings of the 18th international conference on World wide web
    April 2009
    1280 pages
    ISBN:9781605584874
    DOI:10.1145/1526709

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 20 April 2009

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    Author Tags

    1. geographical relevance
    2. human computation
    3. image annotation
    4. image search

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    • (2017)High-Level Context Information for Tasks in TeachingAdvances in Human Factors in Training, Education, and Learning Sciences10.1007/978-3-319-60018-5_27(278-289)Online publication date: 23-Jun-2017
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    • (2015)Recommendations in location-based social networksGeoinformatica10.1007/s10707-014-0220-819:3(525-565)Online publication date: 1-Jul-2015
    • (2015)EgoTR: Personalized Tweets Recommendation ApproachIntelligent Systems in Cybernetics and Automation Theory10.1007/978-3-319-18503-3_23(227-238)Online publication date: 2015
    • (2014)Modeling Paying Behavior in Game Social NetworksProceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management10.1145/2661829.2662024(411-420)Online publication date: 3-Nov-2014
    • (2013)Augmented Reality Interfaces in Human Computation SystemsHandbook of Human Computation10.1007/978-1-4614-8806-4_26(317-331)Online publication date: 20-Nov-2013
    • (2011)Guess who?Proceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/1978942.1979145(1373-1382)Online publication date: 7-May-2011
    • (2011)Drawing on mobile crowds via social mediaMultimedia Systems10.1007/s00530-011-0242-018:1(53-67)Online publication date: 25-Jun-2011
    • (2010)A crowdsourcing based mobile image translation and knowledge sharing serviceProceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia10.1145/1899475.1899481(1-9)Online publication date: 1-Dec-2010

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