Description
Book SynopsisInformation on integrating soft computing techniques into video surveillance is widely scattered among conference papers, journal articles, and books. Bringing this research together in one source, Handbook on Soft Computing for Video Surveillance illustrates the application of soft computing techniques to different tasks in video surveillance. Worldwide experts in the field present novel solutions to video surveillance problems and discuss future trends.
After an introduction to video surveillance systems and soft computing tools, the book gives examples of neural network-based approaches for solving video surveillance tasks and describes summarization techniques for content identification. Covering a broad spectrum of video surveillance topics, the remaining chapters explain how soft computing techniques are used to detect moving objects, track objects, and classify and recognize target objects. The book also explores advanced surveillance systems und
Table of Contents
Introduction to Video Surveillance Systems. The Role of Soft Computing in Image Analysis: Rough-Fuzzy Approach. Neural Networks in Video Surveillance: A Perspective View. Video Summarization and Significance of Content: A Review. Background Subtraction for Visual Surveillance: A Fuzzy Approach. Sensor and Data Fusion: Taxonomy, Challenges, and Applications. Independent Viewpoint Silhouette-Based Human Action Modeling and Recognition. Clustering for Multi-Perspective Video Analytics: A Soft Computing-Based Approach. An Unsupervised Video Shot Boundary Detection Technique Using Fuzzy Entropy Estimation of Video Content. Multi-Robot and Multi-Camera Patrolling. A Network of Audio and Video Sensors for Monitoring Large Environments. Index.
