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Burlai T. (ed.) Face Recognition Across the Imaging Spectrum

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Burlai T. (ed.) Face Recognition Across the Imaging Spectrum
Springer, 2016. — 388.
The book is intended for biometrics researchers, including practitioners and students who either work or plan to become familiar with understanding and processing single-spectral, multispectral, or hyperspectral face images—when captured under controlled or uncontrolled environments, using a variety of imaging sensors, ranging from the state-of-the-art visible and infrared imaging sensors, to the usage of RGB-D and mobile phone image sensors.
The book provides various references for image processing, computer vision, biometrics, and security-focused researchers. The material provides information on current technology including discussion on research areas related to the spectral imaging of human skin, data collection activities, processing and analysis of multispectral and hyperspectral face and iris images, processing of mug shots from ID documents, mobile- and 3D-based face recognition, spoofing attacks, image alterations, score normalization techniques, and multispectral ocular biometrics.
An Overview of Spectral Imaging of Human Skin Toward Face Recognition
Collection of Multispectral Biometric Data for Cross-spectral Identification Applications
Hyperspectral Face Databases for Facial Recognition Research
MWIR-to-Visible and LWIR-to-Visible Face Recognition Using Partial Least Squares and Dictionary Learning
Local Operators and Measures for Heterogeneous Face Recognition
Assessment of Facial Recognition System Performance in Realistic Operating Environments
Understanding Thermal Face Detection: Challenges and Evaluation
Face Recognition Systems Under Spoofing Attacks
On the Effects of Image Alterations on Face Recognition Accuracy
Document to Live Facial Identification
Face Recognition in Challenging Environments: An Experimental and Reproducible Research Survey
Face Recognition with RGB-D Images Using Kinect
Blending 2D and 3D Face Recognition
Exploiting Score Distributions for Biometric Applications
Multispectral Ocular Biometrics
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