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International Journal of Multimedia Information Retrieval
Published in: International Journal of Multimedia Information Retrieval 4/2013

01-11-2013 | Short Paper

Genre-specific modeling of visual features for efficient content based video shot classification and retrieval

Authors: Chiranjoy Chattopadhyay, Amit Kumar Maurya

Published in: International Journal of Multimedia Information Retrieval | Issue 4/2013

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Abstract

This paper presents a genre-specific modeling strategy capable of improving the task of content based video classification and the speed of data retrieval operations. With the ever increasing growth of video data it is important to classify video shots into groups based on its content. For that reason, it is of primary concern to design systems that could automatically classify videos into different genres based on its content. We consider the genre recognition task as a classification problem. We use support vector machines to perform the classification task and propose an improved video classification method. The experimental results show that genre-specific modeling of features can significantly improve the performance. Results have been compared with two contemporary works on video classification, to demonstrate the superiority of our proposed framework.
previous article Event-related image retrieval: exploring geographical and temporal distribution of user tags

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Metadata
Title
Genre-specific modeling of visual features for efficient content based video shot classification and retrieval
Authors
Chiranjoy Chattopadhyay
Amit Kumar Maurya
Publication date
01-11-2013
Publisher
Springer London
Published in
International Journal of Multimedia Information Retrieval / Issue 4/2013
Print ISSN: 2192-6611
Electronic ISSN: 2192-662X
DOI
https://doi.org/10.1007/s13735-013-0034-8

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