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Fuzzy Ontology and Rule based Model for Automatic Semantic Content Extraction from Videos using k-Means Algorithm

by Priyanka Nikam, B.R. Nandwalkar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 130 - Number 13
Year of Publication: 2015
Authors: Priyanka Nikam, B.R. Nandwalkar
10.5120/ijca2015907148

Priyanka Nikam, B.R. Nandwalkar . Fuzzy Ontology and Rule based Model for Automatic Semantic Content Extraction from Videos using k-Means Algorithm. International Journal of Computer Applications. 130, 13 ( November 2015), 11-16. DOI=10.5120/ijca2015907148

@article{ 10.5120/ijca2015907148,
author = { Priyanka Nikam, B.R. Nandwalkar },
title = { Fuzzy Ontology and Rule based Model for Automatic Semantic Content Extraction from Videos using k-Means Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 130 },
number = { 13 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 11-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume130/number13/23268-2015907148/ },
doi = { 10.5120/ijca2015907148 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:25:26.352810+05:30
%A Priyanka Nikam
%A B.R. Nandwalkar
%T Fuzzy Ontology and Rule based Model for Automatic Semantic Content Extraction from Videos using k-Means Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 130
%N 13
%P 11-16
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Video based applications disclosed need for efficiently extracting and modeling the video contents. The video features can be classified into normal data, relative features and logic content. Semantic level understanding is required for core content of video. So to get video content automatic semantic content framework is proposed. In proposed system a semantic content extraction system that allows the user to query and regain objects, events, and concepts that are extracted automatically. VISCOM is a video semantic content model which contains classes and relations between classes. Objects and events are represented by some VISCOM classes and other classes are used in the automatic semantic content extraction framework. VISCOM classes collect the semantic content types and relations. Ontology based fuzzy video data semantic model which uses spatial and temporal relations in event and concept definition is proposed. Extracted objects from consecutive representative frames are processed to extract temporal relations. Additional rules to lower spatial relation computation cost and to define some difficult situations more successfully are used. To extract objects from video we apply k-means clustering algorithm. By, which we get the more relevant objects related to user query.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzziness Ontology Semantic Content Extraction Spatial Relations Video Content Modeling.

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