De Marsico / Nappi / Proença Human Recognition in Unconstrained Environments

Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics
1. Auflage 2017
ISBN: 978-0-08-100712-9
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 248 Seiten

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

Autoren/Hrsg.

De Marsico, Maria

Nappi, Michele

Proença, Hugo Pedro