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IDeixis: image-based Deixis for finding location-based information
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Source Conference on Human Factors in Computing Systems archive
CHI '04 extended abstracts on Human factors in computing systems table of contents
Vienna, Austria
DEMONSTRATION SESSION: Demostrations table of contents
Pages: 781 - 782  
Year of Publication: 2004
ISBN:1-58113-703-6
Authors
Tom Yeh  MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
Konrad Tollmar  MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
Trevor Darrell  MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 6,   Downloads (12 Months): 24,   Citation Count: 2
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ABSTRACT

We demonstrate an image-based approach to specifying location and finding location-based information from camera-equipped mobile devices. We introduce a point-by-photograph paradigm, where users can specify a location simply by taking pictures. Our technique uses content-based image retrieval methods to search the web or other databases for matching images and their source pages to find relevant location-based information. In contrast to conventional approaches to location detection, our method can refer to distant locations and does not require any physical infrastructure beyond mobile internet service. We have developed a prototype on a camera phone and conducted user studies to demonstrate the efficacy of our approach compared to other alternatives.


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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Smith J. and Chang S.. Image and video search engine for the World Wide Web. In Proceedings of Storage and Retrieval for Image and Video Databases (SPIE), pages 84--95, 1997.
 
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Yeh T., Tollmar K. and Darrell T., The IDeixis System, CSAIL Lab report, 2004.


Collaborative Colleagues:
Tom Yeh: colleagues
Konrad Tollmar: colleagues
Trevor Darrell: colleagues