Treffer: Classification of MPEG VBR video data using gradient-based FCM with divergence measure
Title:
Classification of MPEG VBR video data using gradient-based FCM with divergence measure
Authors:
Source:
FSKD 2005 : fuzzy systems and knowledge discovery (Changsha, 27-29 August 2005)Lecture notes in computer science.
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 18 ref 2
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Organisation des mémoires. Traitement des données, Memory organisation. Data processing, Traitement des données. Listes et chaînes de caractères, Data processing. List processing. Character string processing, Intelligence artificielle, Artificial intelligence, Algorithme recherche, Search algorithm, Algoritmo búsqueda, Amas, Cluster, Montón, Analyse amas, Cluster analysis, Analisis cluster, Classification, Clasificación, Divergence, Divergencia, Débit binaire variable, Variable bit rate, Velocidad de bit variable, Fonction densité probabilité, Probability density function, Función densidad probabilidad, Gradient, Gradiente, Mesure distance, Distance measurement, Processus Gauss, Gaussian process, Proceso Gauss, Signal vidéo, Video signal, Señal video, Technique vidéo, Video technique, Técnica video
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Intelligent Computing Research Lab., Dept. of Information Engineering, Myong Ji University, Korea, Republic of
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17135690
Database:
PASCAL Archive
Weitere Informationen
An efficient approximation of the Gaussian Probability Density Function (GPDF) is proposed in this paper. The proposed algorithm, called the Gradient-Based FCM with Divergence Measure (GBFCM (DM)), employs the divergence measurement as its distance measure and utilizes the spatial characteristics of MPEG VBR video data for MPEG data classification problems. When compared with conventional clustering and classification algorithms such as the FCM and GBFCM, the proposed GBFCM(DM) successfully finds clusters and classifies the MPEG VBR data modelled by the 12-dimensional GPDFs.