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Reseach Article

Review Paper on Video Content Analysis into Text Description

Published on December 2015 by Vandana D. Edke, Ramesh M. Kagalkar
National Conference on Advances in Computing
Foundation of Computer Science USA
NCAC2015 - Number 3
December 2015
Authors: Vandana D. Edke, Ramesh M. Kagalkar
8e36ded3-ce75-438a-88b1-780fdeebde37

Vandana D. Edke, Ramesh M. Kagalkar . Review Paper on Video Content Analysis into Text Description. National Conference on Advances in Computing. NCAC2015, 3 (December 2015), 24-28.

@article{
author = { Vandana D. Edke, Ramesh M. Kagalkar },
title = { Review Paper on Video Content Analysis into Text Description },
journal = { National Conference on Advances in Computing },
issue_date = { December 2015 },
volume = { NCAC2015 },
number = { 3 },
month = { December },
year = { 2015 },
issn = 0975-8887,
pages = { 24-28 },
numpages = 5,
url = { /proceedings/ncac2015/number3/23374-5040/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Computing
%A Vandana D. Edke
%A Ramesh M. Kagalkar
%T Review Paper on Video Content Analysis into Text Description
%J National Conference on Advances in Computing
%@ 0975-8887
%V NCAC2015
%N 3
%P 24-28
%D 2015
%I International Journal of Computer Applications
Abstract

This paper reviews video content analysis from the various situations into matter version. The totally different researchers are applied different technique to unravel the approaches. It is a tendency to tend to jointly obtaining down addressing the required down siting extracting the frames from video, comparison the frames; pattern matching and generating the corresponding text description is address here. Hence additionally created a discussion, observation and comparison of quick work applied during this work. It is a tendency to mix the output of progressive object and activity detectors with "real-world" data to pick the foremost probable subject-verb-object triplet for describing a video. It is a tendency to show that this data, mechanically well-mined from web-scale text corpora, hence projected choice rule by providing it discourse information and results in a four-fold increase in activity identification. In contrast to previous ways mentioned in literature survey, therefore in this approach will annotate absolute videos while not requiring the high-priced assortment and annotation of an analogous coaching video corpus.

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Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Generation Concept Hierarchy Semantic Primitive Position/posture And Estimation Of Human Case Frame.