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Discovering Video Structure Using the Pseudo-Semantic Trace

Title: Discovering Video Structure Using the Pseudo-Semantic Trace
Authors: Cuneyt M. Taskiran; Charles A. Bouman; Edward J. Delp
Contributors: The Pennsylvania State University CiteSeerX Archives
Source: http://www.ctaskiran.com/papers/2001_ei.pdf.
Publication Year: 2001
Collection: CiteSeerX
Subject Terms: video database; hidden markov model; pseudo-semantic feature
Description: In this paper we describe a framework of analyzing programs belonging to different TV program genres using Hidden Markov Models and pseudo-semantic features derived from video shots. Clustering using Gaussian mixture models is used to determine the order of the models. Results for initial genre classification experiments using two simple features derived from video shots are given.
Document Type: text
File Description: application/pdf
Language: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.319.5000; http://www.ctaskiran.com/papers/2001_ei.pdf
Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.319.5000; http://www.ctaskiran.com/papers/2001_ei.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Accession Number: edsbas.976D454B
Database: BASE