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Contents: Introduction (J Shen et al.); 3D Articulated Object Understanding, Learning, and Recognition from 2D Images (P S P Wang); On Geometric and Orthogonal Moments (J Shen et al.); Multispectral Image Processing: The Nature Factor (W R Watkins); Detection of Sea Surface Small Targets in Infrared Images Based on Multilevel Filter and Minimum Risk Bayes Test (Y-S Moon et al.); Minimum Description Length Method for Facet Matching (S Maybank & R Fraile); An Integrated Vision System for ALV Navigation (X Ye et al.); Fuzzy Bayesian Networks - A General Formalism for Representation, Inference and

Image processing --- Pattern recognition systems

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Pattern recognition systems --- Pattern perception

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"This edited volume presents a unique multidisciplinary perspective on the problem of visual object categorization. The result of a series of four highly successful workshops on the topic, the book gathers many of the most distinguished researchers from both computer and human vision to reflect on their experience, identify open problems, and foster a cross-disciplinary discussion with the idea that parallel problems and solutions have arisen in both domains. Twenty-seven of these workshop speakers have contributed chapters, including fourteen from computer vision and thirteen from human vision. Their contributions range from broad perspectives on the problem to more specific approaches, collectively providing important historical context, identifying the major challenges, and presenting recent research results. This multidisciplinary collection is the first of its kind on the topic of object categorization, providing an outstanding context for graduate students and researchers in both computer and human vision"--Provided by publisher.

Computer vision. --- Pattern recognition systems.

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Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents. Coverage includes: Data hardware architecture fundamentals Background subtraction of humans in outdoor scenes Camera synchronization Biometric traits: Real-time detection and data segmentation Biometric traits: Feature encoding / matching Fusion at different levels Reaction against security incidents Ethical issues in non-cooperative biometric recognition in public spaces With this book readers will learn how to: Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security Choose the most suited biometric traits and recognition methods for uncontrolled settings Evaluate the performance of a biometric system on real world data Presents a complete picture of the biometric recognition processing chain, ranging from data acquisition to the reaction procedures against security incidents Provides specific requirements and issues behind each typical phase of the development of a robust biometric recognition system Includes a contextualization of the ethical/privacy issues behind the development of a covert recognition system which can be used for forensics and security activities

Biometric identification. --- Computer vision. --- Pattern recognition systems.

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Pattern recognition systems --- Artificial intelligence --- Pattern perception