UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 5 Issue 7
July-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRC006297


Registration ID:
184596

Page Number

1709-1725

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Title

EVENT DETECTION IN SOCCER VIDEO USING BAYESIAN NETOWK

Abstract

Traditionally video were analyzed manually, however this costs valuable time. To sustain increasing growth of video data, there is an emerging demand. Therefore it is necessary to have an approach to make the video analysis task faster and automatically. Automatic video summarization is about extracting important events from original video to produce general summaries for the most important moments by interest. One way for creating a video summary is by extracting the features and then selecting key frames from these segment. Even though this approach is used for automatic video summarization, user cannot retrieve video intuitively, based on high level concepts. To solve this type of problem, event detection based video summarization is proposed in this paper. Proposed event detection approach aims to extract high level events like goal, player exchange and other types using Bayesian network.

Key Words

Video Summarization, Key Frame, Video Skimming, Event Detection, Bayesian Network.

Cite This Article

"EVENT DETECTION IN SOCCER VIDEO USING BAYESIAN NETOWK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.1709-1725, July-2018, Available :http://www.jetir.org/papers/JETIRC006297.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"EVENT DETECTION IN SOCCER VIDEO USING BAYESIAN NETOWK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp1709-1725, July-2018, Available at : http://www.jetir.org/papers/JETIRC006297.pdf

Publication Details

Published Paper ID: JETIRC006297
Registration ID: 184596
Published In: Volume 5 | Issue 7 | Year July-2018
DOI (Digital Object Identifier):
Page No: 1709-1725
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162


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