Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems (Signals and Communication Technology) [Hardcover] review

you're want to buy Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems (Signals and Communication Technology) [Hardcover],yes ..! you comes at the right place. you can get special discount for Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems (Signals and Communication Technology) [Hardcover].You can choose to buy a product and Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems (Signals and Communication Technology) [Hardcover] at the Best Price Online with Secure Transaction Here...





other Customer Rating:






read more Details

This book provides an ample coverage of theoretical and experimental state-of-the-art work also as new trends and directions inside biometrics field. It provides students and software engineers a thorough understanding of how some core low-level foundations of an 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" describes combining data from two or more biometric sensors, for example 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 as well as a brief introduction chapter. The initial part addresses new and emerging face biometrics. Emphasis is put on biometric systems where single sensor and single modality are employed in challenging imaging conditions. The second part on multi-sensory face biometrics deals with all the personal identification task in challenging variable illuminations and outdoor operating scenarios by employing visible and thermal sensors. The third part with the book concentrates on multi-modal face biometrics by integrating voice, ear, and gait modalities with facial data. The final part presents generic chapters on multi-biometrics fusion methodologies and performance prediction techniques.