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Context-based video retrieval system for the life-log applications
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Source International Multimedia Conference archive
Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval table of contents
Berkeley, California
SESSION: Video retrieval table of contents
Pages: 31 - 38  
Year of Publication: 2003
ISBN:1-58113-778-8
Authors
Tetsuro Hori  The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
Kiyoharu Aizawa  The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
Sponsor
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 197,   Citation Count: 7
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ABSTRACT

Recently, we have often heard the terms "Wearable computing" and "Ubiquitous computing". Our expectation for the future of such new computing environments is growing. One of the characteristics of these computing environments is that they embed computers in our lives. In such environments, digitization of personal experiences will be made possible by continuous recordings using a wearable video camera[6, 7]. This could lead to the "automatic life-log application". However, it is evident that the resulting amount of video content will be enormous. Accordingly, to retrieve and browse desired scenes, a vast quantity of video data must be organized using structural information.In this paper, we attempt to develop a "context-based video retrieval system for life-log applications". This wearable system is capable of continuously capturing data not only from a wearable camera and a microphone, but also from various kinds of sensors such as a brain-wave analyzer, a GPS receiver, an acceleration sensor, and a gyro sensor to extract the user's contexts. In addition, the system provides functions that make efficient video browsing and retrieval possible by using data from these sensors and some databases. For example, we can use the following query using this system. "I talked with Kenji while walking at a shopping center in Shinjuku on a cloudy day in mid-May. The conversation was very interesting! I want to see the video of our outing to remember the contents of the conversation."


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.

 
1
K. Aizawa, K. Ishijima, and M. Shiina. Summarizing wearable video. In Proceedings of ICIP 2001, pages 398--401. IEEE, October 2001.
 
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B. Clarkson and A. Pentland. Unsupervised clustering of ambulatory audio and video. In Proceedings of ICASSP'99. IEEE, March 1999.
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Y. Sawahata and K. Aizawa. Wearable imaging system for summarizing personal experiences. In Proceedings of ICME 2003. IEEE, July 2003.

CITED BY  7
 

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Tetsuro Hori: colleagues
Kiyoharu Aizawa: colleagues

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