NDLI: An Optimized Key-Frames Extraction Scheme Based on SVD and Correlation Minimization

Content Provider	IEEE Xplore Digital Library
Author	Ntalianis, K.S. Kollias, S.D.
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens (Ntalianis, K.S.; Kollias, S.D.)
Abstract	In this paper an optimized and efficient technique for keyframes extraction of video sequences is proposed, which leads to selection of a meaningful set of video frames for each given shot. Initially for each frame, the singular value decomposition method is applied and a diagonal matrix is produced, containing the singular values of the frame. Afterwards, a feature vector is created for each frame, by gathering the respective singular values. Next, all feature vectors of the shot are collected to form the feature vectors basin of this shot. Finally, a genetic algorithm approach is proposed and applied to the vectors basin, for locating frames of minimally correlated feature vectors, which are selected as keyframes. Experimental results indicate the promising performance of the proposed scheme on real life video shots
Starting Page	792
Ending Page	795
File Size	315253
Page Count	4
File Format	PDF
ISBN	0780393317
DOI	10.1109/ICME.2005.1521542
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-06
Publisher Place	Netherlands
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Video sequences Singular value decomposition Data mining Genetic algorithms Indexing Content based retrieval Cameras Matrix decomposition Information analysis Feedback genetic algorithm key-frames extraction Singular Value Decomposition correlation criterion
Content Type	Text
Resource Type	Article

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