Space/Time Emerging Face Biometrics.- Pose and Illumination Invariant Face Recognition Using Video Sequences.- Recognizing Faces Across Age Progression.- Quality Assessment and Restoration of Face Images in Long Range/High Zoom Video.- Core Faces: A Shift-Invariant Principal Component Analysis (PCA) Correlation Filter Bank for Illumination-Tolerant Face Recognition.- Multi-Sensory Face Biometrics.- Towards Person Authentication by Fusing Visual and Thermal Face Biometrics.- Multispectral Face Recognition: Fusion of Visual Imagery with Physiological Information.- Feature Selection for Improved Face Recognition in Multisensor Images.- Multimodal Face Biometrics.- Multimodal Face and Speaker Identification for Mobile Devices.- Quo Vadis: 3D Face and Ear Recognition?.- Human Recognition at a Distance in Video by Integrating Face Profile and Gait.- Generic Approaches to Multibiometric Systems.- Fusion Techniques in Multibiometric Systems.- Performance Prediction Methodology for Multibiometric Systems.
This book provides an ample coverage of theoretical and experimental state-of-the-art work as well as new trends and directions in the biometrics field. It offers students and software engineers a thorough understanding of how some core low-level building blocks of a multi-biometric system are implemented. While this book covers a range of biometric traits including facial geometry, 3D ear form, fingerprints, vein structure, voice, and gait, its main emphasis is placed on multi-sensory and multi-modal face biometrics algorithms and systems. Multi-sensory refers to combining data from two or more biometric sensors, such as synchronized reflectance-based and temperature-based face images. Multi-modal biometrics means fusing two or more biometric modalities, like face images and voice timber. This practical reference contains four distinctive parts and a brief introduction chapter. The first part addresses new and emerging face biometrics. Emphasis is placed on biol£™