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Introduction to Intelligent Surveillance [electronic resource] : Surveillance Data Capture, Transmission, and Analytics /

By: Contributor(s): Material type: TextTextSeries: Texts in Computer SciencePublisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 3rd ed. 2019Description: XIII, 222 p. 99 illus., 80 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030107130
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.248 23
LOC classification:
  • TK7882.B56
Online resources:
Contents:
Introduction -- Surveillance Data Capturing and Compression -- Surveillance Data Secure Transmissions -- Surveillance Data Analytics -- Biometrics for Surveillance -- Visual Event Computing I -- Visual Event Computing II -- Surveillance Alarm Making -- Surveillance Computing.
In: Springer Nature eBookSummary: 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 systemand 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.
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Introduction -- Surveillance Data Capturing and Compression -- Surveillance Data Secure Transmissions -- Surveillance Data Analytics -- Biometrics for Surveillance -- Visual Event Computing I -- Visual Event Computing II -- Surveillance Alarm Making -- Surveillance Computing.

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 systemand 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.

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