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Content-enriched classifier for web video classification

Published: 19 July 2010 Publication History

Abstract

With the explosive growth of online videos, automatic real-time categorization of Web videos plays a key role for organizing, browsing and retrieving the huge amount of videos on the Web. Previous work shows that, in addition to text features, content features of videos are also useful for Web video classification. Unfortunately, extracting content features is computationally prohibitive for real-time video classification. In this paper we propose a novel video classification framework that is able to exploit both content and text features for video classification while avoiding the expensive computation of extracting content features at classification time. The main idea of our approach is to utilize the content features extracted from training data to enrich the text based semantic kernels, yielding content-enriched semantic kernels. The content-enriched semantic kernels enable to utilize both content and text features for classifying new videos without extracting their content features. The experimental results show that our approach significantly outperforms the state-of-the-art video classification methods.

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Cited By

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  • (2019)Web video classification with visual and contextual semanticsInternational Journal of Communication Systems10.1002/dac.399432:13Online publication date: 23-Jun-2019
  • (2016)Efficient Web Video Classification via Cross-modality Knowledge TransferringProceedings of the International Conference on Internet Multimedia Computing and Service10.1145/3007669.3007677(211-216)Online publication date: 19-Aug-2016
  • (2014)Bilateral Correspondence Model for Words-and-Pictures Association in Multimedia-Rich MicroblogsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/261138810:4(1-21)Online publication date: 4-Jul-2014
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    cover image ACM Conferences
    SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
    July 2010
    944 pages
    ISBN:9781450301534
    DOI:10.1145/1835449
    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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    Publication History

    Published: 19 July 2010

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    Author Tags

    1. classification
    2. content
    3. text
    4. video
    5. web

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    SIGIR '10 Paper Acceptance Rate 87 of 520 submissions, 17%;
    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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    Cited By

    View all
    • (2019)Web video classification with visual and contextual semanticsInternational Journal of Communication Systems10.1002/dac.399432:13Online publication date: 23-Jun-2019
    • (2016)Efficient Web Video Classification via Cross-modality Knowledge TransferringProceedings of the International Conference on Internet Multimedia Computing and Service10.1145/3007669.3007677(211-216)Online publication date: 19-Aug-2016
    • (2014)Bilateral Correspondence Model for Words-and-Pictures Association in Multimedia-Rich MicroblogsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/261138810:4(1-21)Online publication date: 4-Jul-2014
    • (2011)Improved video categorization from text metadata and user commentsProceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval10.1145/2009916.2010028(835-842)Online publication date: 24-Jul-2011
    • (2010)Topic-based awareness computing model for video-sharing service2010 2nd International Symposium on Aware Computing10.1109/ISAC.2010.5670453(44-50)Online publication date: Nov-2010

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