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High scale video mining with forests of fuzzy decision trees

Published: 28 October 2008 Publication History

Abstract

In this paper, a video mining method based on the use of Forests of Fuzzy Decision Trees (FFDT) is presented. We focus on the use of such a FFDT in a high scale video mining application and highlight the main advantages of using fuzzy set theory in such a process.

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Cited By

View all
  • (2015)Active Learning based on Random Forest and Its Application to Terrain ClassificationProgress in Systems Engineering10.1007/978-3-319-08422-0_41(273-278)Online publication date: 2015
  • (2013)Action Search by Example Using Randomized Visual VocabulariesIEEE Transactions on Image Processing10.1109/TIP.2012.221627322:1(377-390)Online publication date: 1-Jan-2013
  • (2011)Unsupervised random forest indexing for fast action searchProceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition10.1109/CVPR.2011.5995488(865-872)Online publication date: 20-Jun-2011

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Published In

cover image ACM Other conferences
CSTST '08: Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
October 2008
733 pages
ISBN:9781605580463
DOI:10.1145/1456223
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]

Sponsors

  • The French Chapter of ACM Special Interest Group on Applied Computing
  • Ministère des Affaires Etrangères et Européennes
  • Région Ile de France
  • Communauté d'Agglomération de Cergy-Pontoise
  • Institute of Electrical and Electronics Engineers Systems, Man and Cybernetics Society
  • The European Society For Fuzzy And technology
  • Institute of Electrical and Electronics Engineers France Section
  • Laboratoire des Equipes Traitement des Images et du Signal
  • AFIHM: Ass. Francophone d'Interaction Homme-Machine
  • The International Fuzzy System Association
  • Laboratoire Innovation Développement
  • University of Cergy-Pontoise
  • The World Federation of Soft Computing
  • Agence de Développement Economique de Cergy-Pontoise
  • The European Neural Network Society
  • Comité d'Expansion Economique du Val d'Oise

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 October 2008

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Author Tags

  1. TRECVid
  2. forest of fuzzy decision trees
  3. fuzzy decision trees
  4. video mining

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Cited By

View all
  • (2015)Active Learning based on Random Forest and Its Application to Terrain ClassificationProgress in Systems Engineering10.1007/978-3-319-08422-0_41(273-278)Online publication date: 2015
  • (2013)Action Search by Example Using Randomized Visual VocabulariesIEEE Transactions on Image Processing10.1109/TIP.2012.221627322:1(377-390)Online publication date: 1-Jan-2013
  • (2011)Unsupervised random forest indexing for fast action searchProceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition10.1109/CVPR.2011.5995488(865-872)Online publication date: 20-Jun-2011

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