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

By: Hugo Pedro Proenca (Edited by) , Hugo Pedro Proenca (Edited by) , Hugo Pedro Proenca (Edited by) , Hugo Pedro Proenca (Edited by) , Hugo Pedro Proenca (Edited by) , Maria De Marsico (Edited by) , Maria De Marsico (Edited by) , Maria De Marsico (Edited by) , Maria De Marsico (Edited by) , Maria De Marsico (Edited by) , Michele Nappi (Edited by) , Michele Nappi (Edited by) , Michele Nappi (Edited by) , Michele Nappi (Edited by) , Michele Nappi (Edited by)

1 in stock

Ksh 18,100.00

Format: Hardback or Cased Book

ISBN-10: 0081007051

ISBN-13: 9780081007051

Publisher: Elsevier Science & Technology

Imprint: Academic Press Inc.(London) Ltd

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jan 13th, 2017

Publication Status: Active

Product extent: 248 Pages

Weight: 674.00 grams

Dimensions (height x width x thickness): 21.20 x 25.60 x 1.90 cms

Product Classification / Subject(s): Pattern recognition
Pattern recognition

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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
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

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