Human Recognition in Unconstrained Environments (eBook)

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

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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