Shot Transition Detection Based on Locally Linear Embedding

ICMTMA), 2010 International Conference(2010)

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Abstract
Detection of shot transitions servers as the preliminary step to video indexing and retrieval. Locally linear embedding (LLE) algorithm fails when it is applied to video with multi-shot. In this paper, we present a novel framework of shot transitions detection. The method involves two processes: First we extract the manifold feature of shot transition using LLE through addition of virtual frames on an enriched set, and then they are classified by KNN. Experiments show that the recognition rate of shot transition is reached over 90%.
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Key words
locally linear embedding,shot transition,preliminary step,shot transitions detection,knn,linear embedding,mainfold learning,manifold feature,shot boundary detection,shot transitions server,k-nearest neighbor,feature extraction,image classification,video indexing,lle(locally linear embedding),virtual frames,gradual transition,shot transition detection,enriched set,novel framework,recognition rate,video retrieval,image motion analysis,embedded computing,mechatronics,educational technology,k nearest neighbor,manifolds,classification algorithms,automation,computer science education,video compression,image segmentation
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