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Presents a learning technique based on information-theoretic discrimination, which is used to construct face and facial feature detectors. This book also describes a real-time system for face and facial feature detection and tracking in continuous video. It presents a probabilistic framework for embedded face and facial expression recognition.
Face recognition has been actively studied over years. This work provides a comprehensive review of this biometric, especially face recognition from video, assembling a collection of various approaches that are able to recognize human faces under various unconstrained situations. It is useful for researchers and practitioners in the industry.
Human Identification Based on Gait is the first book to address gait as a biometric. This book clearly establishes how human gait is biometric. Human Identification Based on Gait is structured to meet the needs of professionals in industry, as well as advanced-level students in computer science.
Palmprint Authentication is the first book to provide a comprehensive introduction to palmprint technologies. It reveals automatic biometric techniques for personal identification using palmprint, from the approach based on offline palmprint images, to the current state-of-the-art algorithm using online palmprint images.
Details multimodal biometrics and its exceptional utility for increasingly reliable human recognition systems. Reveals the substantial advantages of multimodal systems over conventional identification methods.
Biometrics such as fingerprint, face, gait, iris, voice and signature, recognizes one's identity using his/her physiological or behavioral characteristics. Among these biometric signs, fingerprint has been researched the longest period of time, and shows the most promising future in real-world applications. However, because of the complex distortions among the different impressions of the same finger, fingerprint recognition is still a challenging problem. Computational Algorithms for Fingerprint Recognition presents an entire range of novel computational algorithms for fingerprint recognition. These include feature extraction, indexing, matching, classification, and performance prediction/validation methods, which have been compared with state-of-art algorithms and found to be effective and efficient on real-world data. All the algorithms have been evaluated on NIST-4 database from National Institute of Standards and Technology (NIST). Specific algorithms addressed include:-Learned template based minutiae extraction algorithm, -Triplets of minutiae based fingerprint indexing algorithm, -Genetic algorithm based fingerprint matching algorithm, -Genetic programming based feature learning algorithm for fingerprint classification, -Comparison of classification and indexing based approaches for identification, -Fundamental fingerprint matching performance prediction analysis and its validation.Computational Algorithms for Fingerprint Recognition is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.
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