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Video summarization preserving dynamic content

Published: 28 September 2007 Publication History
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  • Abstract

    This paper describes a system for selecting excerpts from unedited video and presenting the excerpts in a short summary video for efficiently understanding the video contents. Color and motion features are used to divide the video into segments where the color distribution and camera motion are similar. Segments with and without camera motion are clustered separately to identify redundant video. Audio features are used to identify clapboard appearances for exclusion. Representative segments from each cluster are selected for presentation. To increase the original material contained within the summary and reduce the time required to view the summary, selected segments are played back at a higher rate based on the amount of detected camera motion in the segment. Pitch-preserving audio processing is used to better capture the sense of the original audio. Metadata about each segment is overlayed on the summary to help the viewer understand the context of the summary segments in the original video.

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    cover image ACM Conferences
    TVS '07: Proceedings of the international workshop on TRECVID video summarization
    September 2007
    108 pages
    ISBN:9781595937803
    DOI:10.1145/1290031
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 28 September 2007

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    Author Tags

    1. clustering
    2. presentation
    3. segmentation
    4. video summarization

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    MM07
    MM07: The 15th ACM International Conference on Multimedia 2007
    September 28, 2007
    Bavaria, Augsburg, Germany

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    MM '24
    The 32nd ACM International Conference on Multimedia
    October 28 - November 1, 2024
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    Cited By

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    • (2019)A Systematic Review on Literature-based DiscoveryACM Computing Surveys10.1145/336575652:6(1-34)Online publication date: 10-Dec-2019
    • (2019)Applications of Distributed Ledger Technologies to the Internet of ThingsACM Computing Surveys10.1145/335998252:6(1-34)Online publication date: 14-Nov-2019
    • (2019)A Survey of DevOps Concepts and ChallengesACM Computing Surveys10.1145/335998152:6(1-35)Online publication date: 14-Nov-2019
    • (2019)Survey of Compressed Domain Video Summarization TechniquesACM Computing Surveys10.1145/335539852:6(1-29)Online publication date: 16-Oct-2019
    • (2019)A Survey of Metaprogramming LanguagesACM Computing Surveys10.1145/335458452:6(1-39)Online publication date: 16-Oct-2019
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    • (2017)Human Motion Trajectory Analysis Based Video Summarization2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)10.1109/ICMLA.2017.0-103(550-555)Online publication date: Dec-2017
    • (2017)Scalable video summarization via sparse dictionary learning and selection simultaneouslyMultimedia Tools and Applications10.1007/s11042-016-3433-z76:6(7947-7971)Online publication date: 1-Mar-2017
    • (2014)First-person hyper-lapse videosACM Transactions on Graphics10.1145/2601097.260119533:4(1-10)Online publication date: 27-Jul-2014
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