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Most biometric systems employed for human recognition require physical contact with, or close proximity to, a cooperative subject. Far more challenging is the ability to reliably recognize individuals at a distance, when viewed from an arbitrary angle under real-world environmental conditions. Gait and face data are the two biometrics that can be most easily captured from a distance using a video camera. This comprehensive and logically organized text/reference addresses the fundamental problems associated with gait and face-based human recognition, from color and infrared video data that are acquired from a distance. It examines both model-free and model-based approaches to gait-based human recognition, including newly developed techniques where both the model and the data (obtained from multiple cameras) are in 3D. In addition, the work considers new video-based techniques for face profile recognition, and for the super-resolution of facial imagery obtained at different angles. Finally, the book investigates integrated systems that detect and fuse both gait and face biometrics from video data. Topics and features: Discusses a framework for human gait analysis based on Gait Energy Image, a spatio-temporal gait representation Evaluates the discriminating power of model-based gait features using Bayesian statistical analysis Examines methods for human recognition using 3D gait biometrics, and for moving-human detection using both color and thermal image sequences Describes approaches for the integration of face profile and gait biometrics, and for super-resolution of frontal and side-view face images Introduces an objective non-reference quality evaluation algorithm for super-resolved images Presents performance comparisons between different biometrics and different fusion methods for integrating gait and super-resolved face from video This unique and authoritative text is an invaluable resource for researchers and graduate students of computer vision, pattern recognition and biometrics. The book will also be of great interest to professional engineers of biometric systems. Dr. Bir Bhanu is Distinguished Professor of Electrical Engineering, and Director of the Center for Research in Intelligent Systems, at the University of California, Riverside, USA. Dr. Ju Han is a Specialist at the Energy Biosciences Institute, a joint appointment with the Lawrence Berkeley National Laboratory and the University of California, Berkeley, USA.

Mathematical statistics --- Computer. Automation --- patroonherkenning --- beeldverwerking --- factoranalyse --- informatica --- maatschappij

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The advances of live cell video imaging and high-throughput technologies for functional and chemical genomics provide unprecedented opportunities to understand how biological processes work in subcellular and multicellular systems. The interdisciplinary research field of Video Bioinformatics is defined by Bir Bhanu as the automated processing, analysis, understanding, data mining, visualization, query-based retrieval/storage of biological spatiotemporal events/data and knowledge extracted from dynamic images and microscopic videos. Video bioinformatics attempts to provide a deeper understanding of continuous and dynamic life processes. Genome sequences alone lack spatial and temporal information, and video imaging of specific molecules and their spatiotemporal interactions, using a range of imaging methods, are essential to understand how genomes create cells, how cells constitute organisms, and how errant cells cause disease. The book examines interdisciplinary research issues and challenges with examples that deal with organismal dynamics, intercellular and tissue dynamics, intracellular dynamics, protein movement, cell signaling and software and databases for video bioinformatics. Topics and Features · Covers a set of biological problems, their significance, live-imaging experiments, theory and computational methods, quantifiable experimental results and discussion of results. · Provides automated methods for analyzing mild traumatic brain injury over time, identifying injury dynamics after neonatal hypoxia-ischemia and visualizing cortical tissue changes during seizure activity as examples of organismal dynamics · Describes techniques for quantifying the dynamics of human embryonic stem cells with examples of cell detection/segmentation, spreading and other dynamic behaviors which are important for characterizing stem cell health · Examines and quantifies dynamic processes in plant and fungal systems such as cell trafficking, growth of pollen tubes in model systems such as Neurospora Crassa and Arabidopsis · Discusses the dynamics of intracellular molecules for DNA repair and the regulation of cofilin transport using video analysis · Discusses software, system and database aspects of video bioinformatics by providing examples of 5D cell tracking by FARSIGHT open source toolkit, a survey on available databases and software, biological processes for non-verbal communications and identification and retrieval of moth images This unique text will be of great interest to researchers and graduate students of Electrical Engineering, Computer Science, Bioengineering, Cell Biology, Toxicology, Genetics, Genomics, Bioinformatics, Computer Vision and Pattern Recognition, Medical Image Analysis, and Cell Molecular and Developmental Biology. The large number of example applications will also appeal to application scientists and engineers. Dr. Bir Bhanu is Distinguished Professor of Electrical & Computer Engineering, Interim Chair of the Department of Bioengineering, Cooperative Professor of Computer Science & Engineering, and Mechanical Engineering and the Director of the Center for Research in Intelligent Systems, at the University of California, Riverside, California, USA. Dr. Prue Talbot is Professor of Cell Biology & Neuroscience and Director of the Stem Cell Center and Core at the University of California Riverside, California, USA.

Information retrieval --- Biomathematics. Biometry. Biostatistics --- Biological techniques --- Molecular biology --- Biology --- Programming --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- beeldverwerking --- Arabidopsis --- datamining --- bio-informatica --- biologie --- informatica --- informatiesystemen --- moleculaire biologie --- data acquisition

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Mathematical statistics --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- beeldverwerking --- factoranalyse --- grafische vormgeving --- KI (kunstmatige intelligentie) --- robots --- AI (artificiële intelligentie)