• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
搜索

Author:

Zhao, Shi-Wei (Zhao, Shi-Wei.) | Zhuo, Li (Zhuo, Li.) | Sun, Shao-Qing (Sun, Shao-Qing.) | Shen, Lan-Sun (Shen, Lan-Sun.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

A novel classification method of video shot genre based on data-mining is proposed in this paper. First, shot boundary detection and key frames extraction are performed. Second, some visual features such as color and motion are extracted for the key frame and shots. Third, decision tree is applied to discover the rules between these features and shots classes from numerous training data. Finally, these rules are exploited to classify the new video shots. Experimental results show that compared with the method based on SVM (support vector machine), the proposed method can achieve higher detection accuracy and the rules obtained are easy to comprehend.

Keyword:

Decision trees Trees (mathematics) Support vector machines Image segmentation Data mining Extraction

Author Community:

  • [ 1 ] [Zhao, Shi-Wei]Signal and Information Processing Lab., Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Zhuo, Li]Signal and Information Processing Lab., Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Sun, Shao-Qing]Signal and Information Processing Lab., Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Shen, Lan-Sun]Signal and Information Processing Lab., Beijing University of Technology, Beijing 100124, China

Reprint Author's Address:

Show more details

Related Keywords:

Related Article:

Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2012

Issue: 5

Volume: 38

Page: 721-726

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 12

Online/Total:528/10515863
Address:BJUT Library(100 Pingleyuan,Chaoyang District,Beijing 100124, China Post Code:100124) Contact Us:010-67392185
Copyright:BJUT Library Technical Support:Beijing Aegean Software Co., Ltd.