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Human Recognition in Unconstrained Environments
Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics
Hugo Pedro Proença , Maria De Marsico , Michele Nappi
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
- 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
With this book readers will learn how to:
- 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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