Background Modeling and Foreground Detection for Video Surveillance
Seiten
2020
Chapman & Hall/CRC (Verlag)
978-0-367-65911-0 (ISBN)
Chapman & Hall/CRC (Verlag)
978-0-367-65911-0 (ISBN)
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.
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.
Thierry Bouwmans, Fatih Porikli, Benjamin Höferlin, Antoine Vacavant
Introduction and Background. Traditional and Recent Models. Applications in Video Surveillance. Sensors, Hardware, and Implementations. Benchmarking and Evaluation. Index.
| Erscheinungsdatum | 01.10.2020 |
|---|---|
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Gewicht | 1524 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Umwelttechnik / Biotechnologie | |
| ISBN-10 | 0-367-65911-5 / 0367659115 |
| ISBN-13 | 978-0-367-65911-0 / 9780367659110 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
Mehr entdecken
aus dem Bereich
aus dem Bereich
Flugsimulation mit Microsoft Flight Simulator, X-Plane, AeroflyFS und …
Buch | Softcover (2023)
Springer Fachmedien (Verlag)
CHF 48,95
Modelle für 3D-Druck und CNC entwerfen
Buch | Softcover (2022)
dpunkt (Verlag)
CHF 48,85
