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About this book
Exploration of Visual Data presents latest research efforts in the area of content-based exploration of image and video data. The main objective is to bridge the semantic gap between high-level concepts in the human mind and low-level features extractable by the machines.
The two key issues emphasized are "content-awareness" and "user-in-the-loop". The authors provide a comprehensive review on algorithms for visual feature extraction based on color, texture, shape, and structure, and techniques for incorporating such information to aid browsing, exploration, search, and streaming of image and video data. They also discuss issues related to the mixed use of textual and low-level visual features to facilitate more effective access of multimedia data.
Exploration of Visual Data provides state-of-the-art materials on the topics of content-based description of visual data, content-based low-bitrate video streaming, and latest asymmetric and nonlinear relevance feedback algorithms, which to date are unpublished.
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Exploration of Visual Data
Authors: Xiang Sean Zhou, Yong Rui, Thomas S. Huang
Series Title: The International Series in Video Computing
DOI: https://doi.org/10.1007/978-1-4615-0497-9
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2003
Hardcover ISBN: 978-1-4020-7569-8Published: 30 September 2003
Softcover ISBN: 978-1-4613-5106-1Published: 29 October 2012
eBook ISBN: 978-1-4615-0497-9Published: 06 December 2012
Series ISSN: 1571-5205
Edition Number: 1
Number of Pages: XVII, 187
Topics: Image Processing and Computer Vision, Computer Imaging, Vision, Pattern Recognition and Graphics, Artificial Intelligence, Multimedia Information Systems, Data Structures and Information Theory