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

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

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SKU 9780081007051 Categories Products, Sciences And Technology

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 ...

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Description

Product ID:	9780081007051
Product Form:	Hardback
Country of Manufacture:	GB
Title:	Human Recognition in Unconstrained Environments
Subtitle:	Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics
Authors:	Author: Hugo Pedro Proenca, Michele Nappi, Maria De Marsico
Page Count:	248
Subjects:	Pattern recognition, Pattern recognition
Description:	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
Imprint Name:	Academic Press Inc.(London) Ltd
Publisher Name:	Elsevier Science & Technology
Country of Publication:	GB
Publishing Date:	2017-01-13

Additional information

Weight	674 g
Dimensions	212 × 256 × 19 mm

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