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Author:

Cui, Yize (Cui, Yize.) | Cai, Yiheng (Cai, Yiheng.) | Qiu, Changyan (Qiu, Changyan.) | Gao, Xurong (Gao, Xurong.)

Indexed by:

EI Scopus

Abstract:

This paper presents an effective scene-detection approach for unnamed news video. Firstly, we use shot detection based on the hand-craft feature to divide the unnamed news video into shots. Secondly, convolutional neural network and characteristic of host scene were combined to identify the news channel. Finally, we take advantage of the continuity of news video and propose a new scene detection method. Our team has tested the proposed method on a variety of videos including videos from CCTV4, CCTV13, Beijing News, Anhui News and Shanghai News. Comparative analysis shows that our method outperforms the competitor approach using similar experimental settings, which proves the effectiveness of our method on news video scene detection © 2017 IEEE.

Keyword:

Biomedical engineering Feature extraction Convolutional neural networks Image processing

Author Community:

  • [ 1 ] [Cui, Yize]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Cai, Yiheng]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Qiu, Changyan]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Gao, Xurong]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China

Reprint Author's Address:

  • [cui, yize]faculty of information technology, beijing university of technology, beijing; 100124, china

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Source :

Year: 2017

Volume: 2018-January

Page: 1-5

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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