Human Recognition in Unconstrained Environments
Autor: | Maria De Marsico, Michele Nappi, Hugo Pedro Proença |
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EAN: | 9780081007129 |
eBook Format: | PDF/ePUB |
Sprache: | Englisch |
Produktart: | eBook |
Veröffentlichungsdatum: | 09.01.2017 |
Untertitel: | Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics |
Kategorie: | |
Schlagworte: | biometrics machine learning multibiometric approaches multisensor approaches pattern recognition recognition soft biometrics |
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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