Video summarization by Contourlet Transform and structural similarity

Author

Hari, R. ; Wilscy, M.

Author_Institution

Dept. of Electron. & Commn. Eng., Coll. of Eng., Trivandrum, India

fYear

2011

fDate

22-24 Sept. 2011

Firstpage

178

Lastpage

182

Abstract

Video summarization is the main aspect in video content management system, by which users can easily search the video content for a particular data or scene. Video summarization is the process of selecting a set of significant frames called key frames to represent original video in the form of a short video clip. In this work, individual frames of the video represented using Contourlet Transform are analyzed structurally to detect the scene changes, which will result in clustering of frames in the video. Finally Renyi Entropy can be used to extract most relevant frames from clusters to construct full motion summarized video.

Keywords

entropy; pattern clustering; transforms; video signal processing; Renyi entropy; contourlet transform; frame clustering; key frames; structural similarity; video clip; video content management system; video summarization; Clustering algorithms; Entropy; Feature extraction; Filter banks; Indexes; Motion pictures; Transforms; Contourlet Transform; Multi Resolution; Renyi Entropy; Structural Similarity Measure; Video Summarization;

fLanguage

English

Publisher

ieee

Conference_Titel

Recent Advances in Intelligent Computational Systems (RAICS), 2011 IEEE

Conference_Location

Trivandrum

Print_ISBN

978-1-4244-9478-1

Type

conf

DOI

10.1109/RAICS.2011.6069297

Filename

6069297