| ISBN13: | 9780367659110 |
| ISBN10: | 0367659115 |
| Binding: | Paperback |
| No. of pages: | 631 pages |
| Size: | 254x178 mm |
| Weight: | 1524 g |
| Language: | English |
| 242 |
Geometry and topology
Applied mathematics
Electrical engineering and telecommunications, precision engineering
Energy industry
Computer architecture, logic design
Software development
Digital signal, audio and image processing
Environmental sciences
Geometry and topology (charity campaign)
Applied mathematics (charity campaign)
Electrical engineering and telecommunications, precision engineering (charity campaign)
Energy industry (charity campaign)
Computer architecture, logic design (charity campaign)
Software development (charity campaign)
Digital signal, audio and image processing (charity campaign)
Environmental sciences (charity campaign)
Background Modeling and Foreground Detection for Video Surveillance
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This book provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection. It presents the top methods and algorithms for detecting moving objects in video surveillance. It covers statistical models, clustering models, neural networks, and fuzzy models. The book also addresses se
Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements.
Incorporating both established and new ideas, Background Modeling and Foreground Detection for Video Surveillance provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection. Leaders in the field address a wide range of challenges, including camera jitter and background subtraction.
The book presents the top methods and algorithms for detecting moving objects in video surveillance. It covers statistical models, clustering models, neural networks, and fuzzy models. It also addresses sensors, hardware, and implementation issues and discusses the resources and datasets required for evaluating and comparing background subtraction algorithms. The datasets and codes used in the text, along with links to software demonstrations, are available on the book?s website.
A one-stop resource on up-to-date models, algorithms, implementations, and benchmarking techniques, this book helps researchers and industry developers understand how to apply background models and foreground detection methods to video surveillance and related areas, such as optical motion capture, multimedia applications, teleconferencing, video editing, and human?computer interfaces. It can also be used in graduate courses on computer vision, image processing, real-time architecture, machine learning, or data mining.
"? a very interesting, extensive, and up-to-date book about various aspects related to background subtraction for video surveillance systems. It successfully provides a complete overview and an in-depth view? an absolute ?must-read book? for people working in this domain."
?Computing Reviews, June 2015
Introduction and Background. Traditional and Recent Models. Applications in Video Surveillance. Sensors, Hardware, and Implementations. Benchmarking and Evaluation. Index.
