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Graphical Probabilistic Modeling and Applications in Multimedia Content Analysis by Xiao-Ping Zhang; Zhu Liu is a scholarly article available to read on EtoBox.

What is Graphical Probabilistic Modeling and Applications in Multimedia Content Analysis about?

Graphical probabilistic models play an important role in modern machine learning and pattern recognition. In this half-day tutorial, we introduce the fundamentals of graphical probabilistic modeling, including Bayesian networks, Markov random fields, hidden conditional Random field, etc. We also discuss some applications of graphical probabilistic modeling in multimedia content analysis, for example, video segmentation, video event detection, video sequence matching, and image labeling. The audience will learn the basic of graphical models, and get familiar with the state of the art in multimedia content analysis systems.

Author

Xiao-Ping Zhang; Zhu Liu

Publisher

ACM

Published

2011

Language

EN