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Evaluation of video summarization for a large number of cameras in ubiquitous home

Published:06 November 2005Publication History

ABSTRACT

A system for video summarization in a ubiquitous environment is presented. Data from pressure-based floor sensors are clustered to segment footsteps of different persons. Video handover has been implemented to retrieve a continuous video showing a person moving in the environment. Several methods for extracting key frames from the resulting video sequences have been implemented, and evaluated by experiments. It was found that most of the key frames the human subjects desire to see could be retrieved using an adaptive algorithm based on camera changes and the number of footsteps within the view of the same camera. The system consists of a graphical user interface that can be used to retrieve video summaries interactively using simple queries.

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References

  1. Yamazaki, T. Ubiquitous Home: Real-life Testbed for Home Context-Aware Service. In Proceedings of Tridentcom2005, 2005, 54--59. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Sebe, N., Lew, M. S., Zhou, X., Huang, T. S., and Bakker, E. The State of the Art in Image and Video Retrieval. In Proceedings of the International Conf. on Image and Video Retrieval (CIVR'03), 2003, 1--8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Wang, J. R., Prameswaran, N., Yu, X., Xu, C., and Tian, Q. Archiving Tennis Video Clips Based on Tactics Information. In Proceedings of PCM (2), 2004, 314--321. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Haubold, A. and Kender, J. R. Segmentation, Indexing, and Visualization of Extended Instructional Videos. CoRR cs.IR/0302023 (2003).Google ScholarGoogle Scholar
  5. Divakaran, A., Otsuka, I., Radhakrishnan, R., Nakane, K., and Ogawa, M. Audio-Assisted Video Browsing for DVD Recorders. In Proceedings of PCM (2), 2004, 27--33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Morisawa, K., Nitta, N., and Babaguchi, N. Video Scene Retrieval with Sign Sequence Matching Based on Audio Features. In Proceedings of PCM (2), 2004, 121--129. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Davis, M., King, S., and Good, N. From Context to Content: Leveraging Context to Infer Media Metadata. In Proceedings of ACM Multimedia, 2004, 188--195. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Aizawa, K., Kawasaki, S., Ishikawa, T., and Yamasaki, T. Capture and retrieval of life log. In Proceedings of ICAT, 2004, 49--55.Google ScholarGoogle Scholar
  9. Department of Sensory Media - Ubiquitous Sensor Room: http://www.mis.atr.jp/~megumu/IM _Web/MisIM-E.html. ATR Media Information Science Laboratories, Kyoto, Japan.Google ScholarGoogle Scholar
  10. Abowd, G. A., Bobick, I., Essa, I., Mynatt, E., and Rogers, W. The Aware Home: Developing Technologies for Successful Aging. In Proceedings of AAAI, 2002.Google ScholarGoogle Scholar
  11. Orr, R. J., and Abowd, G. D. The Smart Floor: A Mechanism for Natural User Identification and Tracking. In Proceedings of the 2000 Conference on Human Factors in Computing Systems, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Jaimes, A., Omura, K., Nagamine, T., and Hirata, K. Memory Cues for Meeting Video Retrieval. In Proceedings of ACM CARPE Workshop, 2004, 74--85. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Mori, T., Noguchi, H., Takada, A., and Sato, T. Sensing Room: Distributed Sensor Environment for Measurement of Human Daily Behavior. In Proceedings of International Workshop on Networked Sensing Systems, 2004, 40--43.Google ScholarGoogle Scholar
  14. Matsuoka, K., and Fukushima, K. Understanding of Living Activity in a House for Real-time Life Support. In Proceedings of SCIS & ISIS, 2004, 1--6.Google ScholarGoogle Scholar
  15. Liu, L., and Fan, G. Combined Key-frame Extraction and Object-based Video Segmentation. IEEE Trans. Circuits and System for Video Technology, 15, 7 (2005), 869--884. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Naphade, M. R., and Smith, J. R. On the Detection of Semantic Concepts at TRECVID. In Proceedings of ACM Multimedia, 2004, 660--667. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. TRECVID 2005 Guidelines, <http://www-nlpir.nist.gov/ projects/ tv2005/tv2005.html>, National Institute of Standards and Technology, USA, 2005.Google ScholarGoogle Scholar
  18. Kawasaki, S., Ishikawa, T., Yamasaki, T., Aizawa, K. Effective Life-Log Video Summarization Based on Sampling of Sensor Data. In Proceedings of IEICE MVE, 2005.Google ScholarGoogle Scholar
  19. Song, X., and Fan, G. Joint Key-Frame Extraction and Object-Based Video Segmentation. In Proceedings of Motion05 (II), 126--131. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. De Silva, G. C., yamasaki, T., Ishikawa, T., and Aizawa, K. Video Handover for Retrieval in a Ubiquitous Environment Using Floor Sensor Data. In Proceedings of ICME, 2005.Google ScholarGoogle ScholarCross RefCross Ref

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            cover image ACM Conferences
            MULTIMEDIA '05: Proceedings of the 13th annual ACM international conference on Multimedia
            November 2005
            1110 pages
            ISBN:1595930442
            DOI:10.1145/1101149

            Copyright © 2005 ACM

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            • Published: 6 November 2005

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            MULTIMEDIA '05 Paper Acceptance Rate49of312submissions,16%Overall Acceptance Rate995of4,171submissions,24%

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