About this book
The inexpensive collection, storage, and transmission of vast amounts of visual data has revolutionized science, technology, and business. Innovations from various disciplines have aided in the design of intelligent machines able to detect and exploit useful patterns in data. One such approach is statistical learning for pattern analysis.
Among the various technologies involved in intelligent visual information processing, statistical learning and pattern analysis is undoubtedly the most popular and important approach, and is the area which has undergone the most rapid development in recent years. Above all, it provides a unifying theoretical framework for applications of visual pattern analysis.
This unique textbook/reference provides a comprehensive overview of theories, methodologies, and recent developments in the field of statistical learning and statistical analysis for visual pattern modeling and computing. The book describes the solid theoretical foundation, provides a complete summary of the latest advances, and presents typical issues to be considered in making a real system for visual information processing.
• Provides a broad survey of recent advances in statistical learning and pattern analysis with respect to the two principal problems of representation and computation in visual computing
• Presents the fundamentals of statistical pattern recognition and statistical learning via the general framework of a statistical pattern recognition system
• Discusses pattern representation and classification, as well as concepts involved in supervised learning, semi-statistical learning, and unsupervised learning
• Introduces the supervised learning of visual patterns in images, with a focus on supervised statistical pattern analysis, feature extraction and selection, and classifier design
• Covers visual pattern analysis in video, including methodologies for building intelligent video analysis systems, critical aspects of motion analysis, and multi-target tracking formulation for video
• Includes an in-depth discussion of information processing in the cognitive process, embracing a new scheme of association memory and a new architecture for an artificial intelligent system with attractors of chaos
This complete guide to developing intelligent visual information processing systems is rich in examples, and will provide researchers and graduate students in computer vision and pattern recognition with a self-contained, invaluable and useful resource on the topic.
- Book Title Statistical Learning and Pattern Analysis for Image and Video Processing
- Series Title Advances in Pattern Recognition
- DOI https://doi.org/10.1007/978-1-84882-312-9
- Copyright Information Springer London 2009
- Publisher Name Springer, London
- eBook Packages Computer Science Computer Science (R0)
- Hardcover ISBN 978-1-84882-311-2
- Softcover ISBN 978-1-4471-2673-7
- eBook ISBN 978-1-84882-312-9
- Series ISSN 1617-7916
- Edition Number 1
- Number of Pages XVI, 365
- 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
- Buy this book on publisher's site
From the reviews:“The level for which the text was aimed was quite introductory, giving a well executed explanation of not just the technique, but also the supporting techniques. This would serve the book well as a tool to someone learning the technique from new … . Overall I enjoyed the book … . I found that the subjects were well discussed and at a level that suited my knowledge. I would recommend it as a general purpose book for image and video analysis … .” (Gavin Powell, International Association for Pattern Recognition, Vol. 32 (3), July, 2010)