CRC Press, 2015. — 633 p. This handbook solicited contributions to address this 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 model. 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 website1 is provided. This website contains the list of chapters, their abstracts and links to some software demonstrations. It allows the reader to have quick access to the main resources, datasets and codes in the field. 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.
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