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| 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 |
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