Handbook on Soft Computing for Video Surveillance

Handbook on Soft Computing for Video Surveillance

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Features

  • Describes soft computing tools useful in video surveillance, such as neural networks, genetic algorithms, probabilistic reasoning, and the combination of fuzzy and rough sets
  • Includes an introduction to video surveillance systems for beginners
  • Presents methods and algorithms for detecting moving objects in video streams, tracking objects in video sequences, human action modeling and recognition from video sequences, automated video analysis, and detecting video shot boundaries
  • Provides examples of state-of-the-art surveillance systems, including a multi-camera, multi-robot system and a system using multiple audio and video sensors

Summary

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.

Table of Contents

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

Editor Bio(s)

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.

 
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