Intelligent Video Surveillance

This book will provide an overview of techniques for visual monitoring including video surveillance and human activity understanding. It will present the basic techniques of processing video from static cameras, starting with object detection and tracking. The author will introduce further video analytic modules including face detection, trajectory analysis and object classification. Examining system design and specific problems in visual surveillance, such as the use of multiple cameras and moving cameras, the author will elaborate on privacy issues focusing on approaches where automatic processing can help protect privacy.

From the streets of London to subway stations in New York City, hundreds of thousands of surveillance cameras ubiquitously collect hundreds of thousands of videos, often running 24/7. How can such vast volumes of video data be stored, analyzed, indexed, and searched? How can advanced video analysis and systems autonomously recognize people and

Offering ready access to the security industry’s cutting-edge digital future, Intelligent Network Video provides the first complete reference for all those involved with developing, implementing, and maintaining the latest surveillance systems. Pioneering expert Fredrik Nilsson explains how IP-based video surveillance systems provide better image quality, and a more scalable and flexible system at lower cost. A complete and practical reference for all those in the field, this volume: Describes all components relevant to modern IP video surveillance systems Provides in-depth information about image, audio, networking, and compression technologies Discusses intelligent video architectures and applications Offers a comprehensive checklist for those designing a network video system, as well as a systems design tool on DVD Nilsson guides readers through a well-organized tour of the building blocks of modern video surveillance systems, including network cameras, video encoders, storage, servers, sensors, and video management. From there, he explains intelligent video, looking at the architectures and typical applications associated with this exciting technology. Taking a hands-on approach that meets the needs of those working in the industry, this timely volume, illustrated with more than 300 color photos, supplies readers with a deeper understanding of how surveillance technology has developed and, through application, demonstrates why its future is all about intelligent network video.

Continuing in the tradition of the bestselling first edition, this book examines networked surveillance video solutions. It provides the latest details on industry hardware, software, and networking capabilities of the latest cameras and DVRs. It addresses in full detail updated specifications on MPEG-4 and other digital video formats, resolution advantages of analog v. digital, intelligent video capabilities, frame rate control, and indoor/outdoor installations factors. New chapters include cloud computing, standards, and thermal cameras.

Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the shop; and what are the frequent paths), and to measure operational efficiency for improving customer experience. Video analytics has the enormous potential for non-security oriented commercial applications. This book presents the latest developments on video analytics for business intelligence applications. It provides both academic and commercial practitioners an understanding of the state-of-the-art and a resource for potential applications and successful practice.

The goal of Intelligent video surveillance systems is to efficiently extract useful information from a considerable number of videos collected by surveillance cameras by automatically detecting, tracking and recognizing objects of interest, and understanding and analyzing their activities. Video surveillance has a huge amount of applications, from public to private places. These applications require monitoring indoor and outdoor scenes. Nowadays, there are a considerable number of digital surveillance cameras collecting a huge amount of data on a daily basis. Researchers are urged to develop intelligent systems to efficiently extract and visualize useful information from this big data source. The exponential effort on the development of new algorithms and systems for video surveillance is confirmed by the amount of effort invested in projects and companies, the creation on new startups worldwide and, not less important, in the quantity and quality of the manuscripts published in a considerable number of journals and conferences worldwide. This book is an outcome of research done by several researchers who have highly contributed to the field of Video Surveillance. The main goal is to present recent advances in this important topic for the Image Processing community.

Surveillance systems have become increasingly popular. Full involvement of human operators has led to shortcomings, e.g. high labor cost, limited capability for multiple screens, inconsistency in long-duration, etc. Intelligent surveillance systems (ISSs) can supplement or even replace traditional ones. In ISSs, computer vision, pattern recognition, and artificial intelligence technologies are used to identify abnormal behaviours in videos. They present the development of real-time behaviour-based intelligent surveillance systems. The book focuses on the detection of individual abnormal behaviour based on learning and the analysis of dangerous crowd behaviour based on texture and optical flow. Practical systems include a real-time face classification and counting system, a surveillance robot system that utilizes video and audio information for intelligent interaction, and a robust person counting system for crowded environments.

Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.