Handbook on "Background Modeling and Foreground Detection for Video Surveillance"
Résumé
This handbook solicited contributions to address these wide range of challenges met in background modeling and foreground detection for video-surveillance. Thus, it groups the works of the leading teams in this field over the recent years. By incorporating both existing and new ideas, this handbook gives a complete overview of the concepts, theories, algorithms, and applications related to background modeling and foreground detection. First, an introduction to background modeling and foreground detection for beginners is provided by surveying statistical models, clustering models, neural networks and fuzzy models. Furthermore, leading methods and algorithms for detecting moving objects in video surveillance are presented. A description of recent complete datasets and codes are given. Moreover, an accompanying website is provided. Finally, with this handbook, we aim to bring a one-stop solution, i.e., access to a number of different models, algorithms, implementations and benchmarking techniques in a single volume. The handbook consists of five parts.
This website contains the list of chapters, their abstract and links to the demos. It allows the reader to have a quick access to the main resources, datasets and codes in the field.