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A Novel Feature Weighted Clustering Algorithm Based on Rough Sets for Shot Boundary Detection

  • Conference paper
Fuzzy Systems and Knowledge Discovery (FSKD 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4223))

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Abstract

Shot boundary detection as the crucial step attracts much more research interests in recent years. To partition news video into shots, many metrics were constructed to measure the similarity among video frames based on all the available video features. However, too many features will reduce the efficiency of the shot boundary detection. Therefore, it is necessary to perform feature reduction before shot boundary detection. For this purpose, the classification method based on clustering algorithm of Variable Precision Rough-Fuzzy Sets and Variable Precision Rough Sets for feature reduction and feature weighting is proposed. According to the particularity of news scenes, shot transition can be divided into three types: cut transition, gradual transition and no transition. The efficiency of the proposed method is extensively tested on UCI data sets and more than 3 h of news programs and 96.2% recall with 96.3% precision have been achieved.

This work was supported by the program for New Century Excellent Talents in University of China(NCET-04-0948), National Natural Science Foundation of China (No.60202004) and the Key Project of Chinese Ministry of Education (No.104173).

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Author information

Authors and Affiliations

  1. School of Electronic Engineering, Xidian Univ., Xi’an, 710071, China

    Bing Han, Xinbo Gao & Hongbing Ji

Authors
  1. Bing Han
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  2. Xinbo Gao
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  3. Hongbing Ji
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University,, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Life Science Research Center, School of Electronic Engineering, Xidian University,, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  3. School of Electrical and Electronic Engineering, Xidian University, 710071, Xi’an, China

    Guanming Shi

  4. School of Information Technology and Electrical Engineering, The University of Queensland, 4072, Brisbane, Queensland, Australia

    Xue Li

  5. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

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© 2006 Springer-Verlag Berlin Heidelberg

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Han, B., Gao, X., Ji, H. (2006). A Novel Feature Weighted Clustering Algorithm Based on Rough Sets for Shot Boundary Detection. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_55

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  • DOI: https://doi.org/10.1007/11881599_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45916-3

  • Online ISBN: 978-3-540-45917-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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