Handbook on Soft Computing for Video Surveillance

Information 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 under development. Incorporating both existing and new ideas, this handbook unifies the basic concepts, theories, algorithms, and applications of soft computing. It demonstrates why and how soft computing methodologies can be used in various video surveillance problems.

Introduction to Video Surveillance Systems, Tomi D. Räty The Role of Soft Computing in Image Analysis: Rough-Fuzzy Approach, Alessio Ferone, Sankar K. Pal, and Alfredo Petrosino Neural Networks in Video Surveillance: A Perspective View, Lucia Maddalena and Alfredo Petrosino Video Summarization and Significance of Content: A Review, Rajarshi Pal, Ashish Ghosh, and Sankar K. Pal Background Subtraction for Visual Surveillance: A Fuzzy Approach, Thierry Bouwmans Sensor and Data Fusion: Taxonomy, Challenges, and Applications, Lawrence A. Klein, Lyudmila Mihaylova, and Nour-Eddin El Faouzi Independent Viewpoint Silhouette-Based Human Action Modeling and Recognition, Carlos Orrite, Francisco Martínez-Contreras, Elías Herrero, Hossein Ragheb, and Sergio A. Velastin Clustering for Multi-Perspective Video Analytics: A Soft Computing-Based Approach, Ayesha Choudhary, Santanu Chaudhury, and Subhashis Banerjee An Unsupervised Video Shot Boundary Detection Technique Using Fuzzy Entropy Estimation of Video Content, Biswanath Chakraborty, Siddhartha Bhattacharyya, and Paramartha Dutta Multi-Robot and Multi-Camera Patrolling, Christopher King, Maria Valera, Raphael Grech, Robert Mullen, Paolo Remagnino, Luca Iocchi, Luca Marchetti, Daniele Nardi, Dorothy Monekosso, and Mircea Nicolescu A Network of Audio and Video Sensors for Monitoring Large Environments, Claudio Piciarelli, Sergio Canazza, Christian Micheloni, and Gian Luca Foresti Index

Sankar K. Pal is a distinguished scientist and former director of the Indian Statistical Institute. He is a J.C. Bose Fellow of the government of India and a fellow of IEEE, TWAS, IAPR, and IFSA. Dr. Pal has authored more than 400 research publications and has been a recipient of the S.S. Bhatnagar Prize of India. His research interests include pattern recognition and machine learning, image processing, data mining and web intelligence, soft computing, neural nets, genetic algorithms, fuzzy and rough sets, and bioinformatics. Alfredo Petrosino is an associate professor of computer science at the University of Naples Parthenope. He is a senior member of IEEE and a member of IAPR and INNS. Mr. Petrosino has authored more than 100 research publications and has been a recipient of the Academic Price for Cybernetics from the Italian Academy of Science, Arts, and Literature. His research interests include computer vision, image and video analysis, pattern recognition, neural networks, fuzzy and rough sets, and data mining. Lucia Maddalena is a researcher at the Institute for High-Performance Computing and Networking of the National Research Council of Italy. Dr. Maddalena is a member of IEEE and IAPR and an associate editor of the International Journal of Biomedical Data Mining. Her research interests include image processing and multimedia systems in high-performance computational environments.