Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Motion recovery for video content classification
ACM Transactions on Information Systems (TOIS) - Special issue on video information retrieval
Pattern recognition using neural networks: theory and algorithms for engineers and scientists
Pattern recognition using neural networks: theory and algorithms for engineers and scientists
Workload models of VBR video traffic and their use in resource allocation policies
IEEE/ACM Transactions on Networking (TON)
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Statistical characteristics and multiplexing of MPEG streams
INFOCOM '95 Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 2)-Volume - Volume 2
MPEG VBR video traffic modeling and classification using fuzzy technique
IEEE Transactions on Fuzzy Systems
Centroid neural network for unsupervised competitive learning
IEEE Transactions on Neural Networks
Weighted centroid neural network for edge preserving image compression
IEEE Transactions on Neural Networks
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This paper describes how the covariance information in MPEG video data can be incorporated into a distance measure and applies the resulting divergence measure to video content classification problems. The divergence measure is adopted into two different clustering algorithms, the Centroid Neural Network (CNN) and the Gradient Based Fuzzy c-Means (GBFCM) for MPEG video data classification problems, movie or sports. Experiments on 16 MPEG video traces show that the divergence measure with covariance information can decrease the False Alarm Rate (FAR) in classification as much as 46.6% on average.