- Full Description
This textbook provides an 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: presents the fundamentals of statistical pattern recognition and statistical learning; discusses pattern representation and classification; provides a broad survey of recent advances in statistical learning and pattern analysis; introduces the supervised learning of visual patterns in images; covers visual pattern analysis in video; includes an in-depth discussion of information processing in the cognitive process. This guide to intelligent visual information processing systems is rich in examples, and will provide researchers and graduate students with a self-contained survey of the topic.
- Table of Contents
Table of Contents
- Basics in Statistical Pattern Analysis.
- Pattern Representation: Regimes of Modeling.
- Statistical Models of Visual Patterns.
- Learning from Visual Data.
- Statistical Motion Analysis.
- Motion Texture.
- temporal Corresponding in Video.
- Multiple Visual Objects Tracking.
- Video Segmentation.
- based Video Compression.
- Video Analysis Frontier.
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