NDLI: On video textures generation: A comparison between different dimensionality reduction techniques

Content Provider	IEEE Xplore Digital Library
Author	Wentao Fan Bouguila, N.
Copyright Year	2009
Description	Author affiliation: Institute for Information Systems Engineering, University of Concordia, Montreal, Canada (Wentao Fan; Bouguila, N.)
Abstract	Video texture is a new type of medium which can provide a new video with a continuously varying stream of images from a recorded video. It is created by reordering the input video frames in a way which can be played without any visual discontinuity. Recently, a new method of generating video textures has been proposed. It first apply principal components analysis (PCA) to extract signatures or patterns from the original video sequence, and then implement an autoregressive process (AR) model to synthesize new video textures. In this paper, we extend this video texture generation method by comparing PCA with other dimensionality reduction techniques such as probabilistic principal components analysis, kernel principal components analysis, independent component analysis, local linear embedding and Isomap. According to our experiments, these approaches prevail the original approach by providing us video textures with better quality.
Starting Page	5134
Ending Page	5139
File Size	613879
Page Count	6
File Format	PDF
ISBN	9781424427932
ISSN	1062922X
DOI	10.1109/ICSMC.2009.5346016
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Principal component analysis Streaming media Autoregressive processes Kernel Independent component analysis Computer vision Rendering (computer graphics) Cybernetics USA Councils Videoconference autoregressive process Video texture computer vision dimensionality reduction
Content Type	Text
Resource Type	Article

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