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This accessible textbook/reference reviews the fundamental concepts and practical issues involved in designing digital surveillance systems that fully exploit the power of intelligent computing techniques. The book presents comprehensive coverage of all aspects of such systems, from camera calibration and data capture, to the secure transmission of surveillance data. In addition to the detection and recognition of objects and biometric features, the text also examines the automated observation of surveillance events, and how this can be enhanced through the use of deep learning methods and supercomputing technology. This updated new edition features extended coverage on face detection, pedestrian detection and privacy preservation for intelligent surveillance. 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, classroom-tested textbook is ideal for undergraduate and postgraduate-level courses on intelligent surveillance. Researchers 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.

Computer science. --- Computer communication systems. --- Pattern recognition. --- Computer Science. --- Pattern Recognition. --- Computer Communication Networks. --- Optical pattern recognition. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Electronic surveillance. --- 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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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. .

Optical data processing. --- Machine learning. --- Computer science—Mathematics. --- Artificial intelligence. --- Neural networks (Computer science) . --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Machine Learning. --- Mathematics of Computing. --- Artificial Intelligence. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- 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 --- Learning, Machine --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment --- Image processing --- Computer vision. --- Computer science --- Neural networks (Computer science). --- Digital techniques. --- Mathematics. --- Computer mathematics --- Mathematics --- Machine vision --- Vision, Computer --- Pattern recognition systems --- Digital image processing --- Digital electronics --- Neural networks (Computer science)

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Visual cryptography is a secret sharing technique which allows the encryption of an image without requiring any complex computation or knowledge of cryptography. This unique text/reference describes the fundamental concepts, theories and practice of visual cryptography. The design, construction, analysis, and application of visual cryptography schemes (VCSs) are discussed in detail. Original, cutting-edge research is presented on probabilistic, size invariant, threshold, concolorous, and cheating immune VCS. Topics and features: Provides a thorough introduction to the field of visual cryptography Examines various common problems in visual cryptography, including the alignment, flipping, cheating, distortion, and thin line problems Reviews a range of visual cryptography schemes, including XOR-based visual cryptography and security enriched VCS Describes different methods for presenting color content using visual cryptographic techniques Covers such applications of visual cryptography as watermarking, resolution variant VCS, and multiple resolution VCS This logically-structured and comprehensive work will serve as a helpful reference for all researchers and students interested in document authentication and cryptography, including those involved in digital image processing, image watermarking, and media-based security technology. Dr. Feng Liu is an Associate Professor at the Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China. Dr. Wei Qi Yan is a Senior Lecturer in the School of Computing and Mathematical Sciences at Auckland University of Technology, New Zealand.

Data encryption (Computer science) --- Image processing --- Digital techniques. --- Digital image processing --- Digital electronics --- Data encoding (Computer science) --- Encryption of data (Computer science) --- Computer security --- Cryptography --- Computer vision. --- Computer security. --- Coding theory. --- Image Processing and Computer Vision. --- Systems and Data Security. --- Coding and Information Theory. --- Data compression (Telecommunication) --- Information theory --- Machine theory --- Signal theory (Telecommunication) --- Computer programming --- 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 --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Protection --- Security measures --- Optical data processing. --- Information theory. --- Communication theory --- Communication --- Cybernetics --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Optical equipment

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This volume constitutes the refereed proceedings, presented during the ACPR 2019 Workshops, held in Auckland, New Zealand, in November 2019. The 17 full papers and 6 short papers were carefully reviewed and selected out of numerous submissions. The papers are organized according to the topics of the workshops: computer vision for modern vehicles; advances and applications on generative deep learning models; image and pattern analysis for multidisciplinary computational anatomy; multi-sensor for action and gesture recognition; towards the automatic data processing chain for airborne and spaceborne sensors. .

Pattern recognition. --- Computers. --- Computer organization. --- Machine learning. --- Optical data processing. --- Application software. --- Pattern Recognition. --- Information Systems and Communication Service. --- Computer Systems Organization and Communication Networks. --- Machine Learning. --- Image Processing and Computer Vision. --- Computer Applications. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Learning, Machine --- Artificial intelligence --- Machine theory --- Organization, Computer --- Electronic digital computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Optical equipment --- Pattern recognition systems

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This book constitutes the proceedings of the 37th International Conference, IVCNZ 2022, which took place in Auckland, New Zealand, in November 2022. The 37 papers (14 accepted for long oral presentation, 23 for short oral presentation) included in this volume were carefully reviewed and selected from 79 submissions. The conference presents papers on all aspects of computer vision, image processing, computer graphics, virtual and augmented reality, visualization, and HCI applications related to these fields.

Computer vision --- Image processing --- Digital techniques