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Human Recognition in Unconstrained Environments : Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics by Maria De Marsico, Michele Nappi, Hugo Pedro Proença is a nonfiction available to read on EtoBox.

What is Human Recognition in Unconstrained Environments : Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics about?

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

Who reads Human Recognition in Unconstrained Environments : Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics?

Author

Maria De Marsico, Michele Nappi, Hugo Pedro Proença

Publisher

Academic Press, an imprint of Elsevier

Published

2017

Language

EN

ISBN

9780081007129

Category

nonfiction

Subjects

Computer Science, Engineering, Cybernetics