Statistical Learning and Pattern Analysis for Image and Video Processing

Beschreibung:

This textbook is an overview of theories, methodologies, and recent developments in the field, covering the theoretical foundation and providing a complete summary of the latest advances. It also presents key issues to be considered in making a real system. Series: Advances in Computer Vision and Pattern Recognition. Num Pages: 381 pages, 10 black & white tables, biography. BIC Classification: UYQP. Category: (P) Professional & Vocational. Dimension: 239 x 166 x 29. Weight in Grams: 806. . 2009. Hardback. . . . . Books ship from the US and Ireland. Bestandsnummer des Verkäufers V9781848823112

Diesen Artikel melden

Inhaltsangabe:

Von der hinteren Coverseite:

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.

Features:

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.