A Novel Feature Weighted Clustering Algorithm Based on Rough Sets for Shot Boundary Detection
- Bing HanAffiliated withSchool of Electronic Engineering, Xidian Univ.
- , Xinbo GaoAffiliated withSchool of Electronic Engineering, Xidian Univ.
- , Hongbing JiAffiliated withSchool of Electronic Engineering, Xidian Univ.
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.
- A Novel Feature Weighted Clustering Algorithm Based on Rough Sets for Shot Boundary Detection
- Book Title
- Fuzzy Systems and Knowledge Discovery
- Book Subtitle
- Third International Conference, FSKD 2006, Xi’an, China, September 24-28, 2006. Proceedings
- pp 471-480
- Print ISBN
- Online ISBN
- Series Title
- Lecture Notes in Computer Science
- Series Volume
- Series ISSN
- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- Additional Links
- Industry Sectors
- eBook Packages
- Editor Affiliations
- 18. School of Electrical and Electronic Engineering, Nanyang Technological University,
- 19. Life Science Research Center, School of Electronic Engineering, Xidian University,
- 20. School of Electrical and Electronic Engineering, Xidian University
- 21. School of Information Technology and Electrical Engineering, The University of Queensland
- 22. College of Mathematics and Information Science, Hebei Normal University
- Author Affiliations
- 23. School of Electronic Engineering, Xidian Univ., Xi’an, 710071, China
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