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This concise textbook/reference examines the fundamental aspects of intelligent computing for surveillance systems, from camera calibration and data capturing, to secure data transmission. The text covers digital surveillance from the level of an individual object or biometric feature, to the full lifecycle of an event. This is followed by a detailed discussion on how an intelligent system can independently monitor and learn from an event, and invite human input when necessary. The book concludes with a presentation on how the computation speed of the system can be enhanced through the use of supercomputing technology. Topics and features: Contains exercises at the end of every chapter, and a glossary of important terms Provides a thorough introduction to the fundamentals of intelligent surveillance, including surveillance data capture and surveillance data compression Covers the key issues of computer network infrastructure, security, monitoring and forensics, and the essential aspects of object analysis Presents a detailed review of algorithms for surveillance data analytics using biometric features Introduces the concept of surveillance events, and discusses how artificial intelligence can be used for the automated observation and understanding of such events Reviews algorithms that apply decision-making approaches to determine the need for triggering an alarm to alert a member of security staff Describes the use of cutting-edge supercomputing technologies for digital surveillance, such as FPGA, GPU and parallel computing This accessible work serves as a classroom-tested textbook on intelligent surveillance for undergraduate and postgraduate students, as well as a self-study reference for researchers entering this area. Dr. Wei Qi Yan is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title Visual Cryptography for Image Processing and Security.

Electrical Engineering --- Computer Science --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Optical pattern recognition. --- Computer Communication Networks. --- Pattern Recognition. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Electronic surveillance. --- Computer security. --- Pattern recognition. --- Computer communication systems. --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Distributed processing

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This practically-oriented textbook introduces the fundamentals of designing digital surveillance systems powered by intelligent computing techniques. The text offers comprehensive coverage of each aspect of the system, from camera calibration and data capture, to the secure transmission of surveillance data, in addition to the detection and recognition of individual biometric features and objects. The coverage concludes with the development of a complete system for the automated observation of the full lifecycle of a surveillance event, enhanced by the use of artificial intelligence and supercomputing technology. This updated third edition presents an expanded focus on human behavior analysis and privacy preservation, as well as deep learning methods. Topics and features: Contains review questions and exercises in every chapter, together with a glossary Describes the essentials of implementing an intelligent surveillance system and analyzing surveillance data, including a range of biometric characteristics Examines the importance of network security and digital forensics in the communication of surveillance data, as well as issues of issues of privacy and ethics Discusses the Viola-Jones object detection method, and the HOG algorithm for pedestrian and human behavior recognition Reviews the use of artificial intelligence for automated monitoring of surveillance events, and decision-making approaches to determine the need for human intervention Presents a case study on a system that triggers an alarm when a vehicle fails to stop at a red light, and identifies the vehicle’s license plate number Investigates the use of cutting-edge supercomputing technologies for digital surveillance, such as FPGA, GPU and parallel computing This concise and accessible work serves as a classroom-tested textbook for graduate-level courses on intelligent surveillance. Researchers and engineers interested in entering this area will also find the book suitable as a helpful self-study reference. Dr. Wei Qi Yan is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title Visual Cryptography for Image Processing and Security.

Biometrics. --- Artificial intelligence. --- Computer security. --- Computer Communication Networks. --- Artificial Intelligence. --- Systems and Data Security. --- Computer privacy --- Computer system security --- Computer systems --- Computers --- Cyber security --- Cybersecurity --- Electronic digital computers --- Protection of computer systems --- Security of computer systems --- Data protection --- Security systems --- Hacking --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Protection --- Security measures --- Biometrics (Biology). --- Computer communication systems. --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Distributed processing --- Statistical methods

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Big data. --- Computer science. --- Data mining.

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This practically-oriented textbook introduces the fundamentals of designing digital surveillance systems powered by intelligent computing techniques. The text offers comprehensive coverage of each aspect of the system, from camera calibration and data capture, to the secure transmission of surveillance data, in addition to the detection and recognition of individual biometric features and objects. The coverage concludes with the development of a complete system for the automated observation of the full lifecycle of a surveillance event, enhanced by the use of artificial intelligence and supercomputing technology. This updated third edition presents an expanded focus on human behavior analysis and privacy preservation, as well as deep learning methods. Topics and features: Contains review questions and exercises in every chapter, together with a glossary Describes the essentials of implementing an intelligent surveillance system and analyzing surveillance data, including a range of biometric characteristics Examines the importance of network security and digital forensics in the communication of surveillance data, as well as issues of issues of privacy and ethics Discusses the Viola-Jones object detection method, and the HOG algorithm for pedestrian and human behavior recognition Reviews the use of artificial intelligence for automated monitoring of surveillance events, and decision-making approaches to determine the need for human intervention Presents a case study on a system that triggers an alarm when a vehicle fails to stop at a red light, and identifies the vehicle’s license plate number Investigates the use of cutting-edge supercomputing technologies for digital surveillance, such as FPGA, GPU and parallel computing This concise and accessible work serves as a classroom-tested textbook for graduate-level courses on intelligent surveillance. Researchers and engineers interested in entering this area will also find the book suitable as a helpful self-study reference. Dr. Wei Qi Yan is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title Visual Cryptography for Image Processing and Security.

Biomathematics. Biometry. Biostatistics --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- biomathematica --- deep learning --- object recognition --- biostatistiek --- informatica --- biometrie --- computerbeveiliging --- KI (kunstmatige intelligentie) --- parallel processing --- computernetwerken --- AI (artificiële intelligentie)

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Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations. Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms. As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers. This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision. Dr. Wei Qi Yan is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title, Visual Cryptography for Image Processing and Security. .

Mathematics --- Computer science --- Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- computervisie --- neuronale netwerken --- grafische vormgeving --- informatica --- programmeren (informatica) --- wiskunde --- KI (kunstmatige intelligentie) --- AI (artificiële intelligentie)