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low-bitrate video streaming, and latest asymmetric and nonlinear relevance feedback algorithms, which to date are unpublished.
- Book Title Exploration of Visual Data
- Series Title The Springer International Series in Video Computing
- DOI https://doi.org/10.1007/978-1-4615-0497-9
- Copyright Information Kluwer Academic Publishers 2003
- Publisher Name Springer, Boston, MA
- eBook Packages Springer Book Archive
- Hardcover ISBN 978-1-4020-7569-8
- Softcover ISBN 978-1-4613-5106-1
- eBook ISBN 978-1-4615-0497-9
- Series ISSN 1571-5205
- Edition Number 1
- Number of Pages XVII, 187
- Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
Image Processing and Computer Vision
Computer Imaging, Vision, Pattern Recognition and Graphics
Multimedia Information Systems
Data Structures and Information Theory
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