Machine Learning for Multimedia Content Analysis
Publication year: 2008
ISBN: 978-0-387-69942-4
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Challenges in complexity and variability of multimedia data have led to revolutions in machine learning techniques. Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. A number of pixels in a digital image collectively conveys certain visual content to viewers. A TV video program consists of both audio and image streams that unfold the underlying story. To recognize the visual content of a digital image, or to understand the underlying story of a video program, we may need to label sets of pixels or groups of image and audio frames jointly.
Subject: Computer Science, DOM Dimensionsreduktion, Gong, Hidden Markov Model Machine Learning Maximum Margin Markov (M3) networks, Multimedia, Simulation, Support Vector Machine, Techniques, Technology, algorithms, complexity, learning, networks, Multimedia Information Systems, Artificial Intelligence, Computer Applications, Information Storage and Retrieval, Database Management, Computer Graphics
