Fredrik Nilsson General Manager, Axis Communications
Network video allows for new capabilities in the surveillance industry that were not feasible in an analog environment, either because they were impossible to implement, or just too cumbersome. Some of the hottest new technologies available in a network video installation are intelligent video, megapixel cameras, and something called immersive imaging.
Today, far more video is being recorded than anyone could ever monitor or search. Studies from the Sandia National Laboratories, which develops science-based technologies to support U.S. national security, suggest that personnel can only watch one monitor for up to 20 minutes before losing focus. Without some form of built-in algorithm compiling relevant information, there is simply no way to monitor all the surveillance cameras in a system - unless you've got an almost unlimited budget.
That's where video analytics enters the picture. Intelligent video (IV), the next big trend in video surveillance, will allow cameras to monitor events within the field of view. Advanced network cameras can have built-in motion detection and event handling. In addition, more intelligent algorithms, such as automatic number plate recognition (a.k.a. license plate recognition) and people counting, are being integrated into security and surveillance systems. Network cameras and IV have important synergies that make the systems more reliable and effective than those using analog cameras with a digital video recorder (DVR) or other centralized system.
Intelligent Video Defined
Different vendors have referred to IV by various terms including "actionable intelligence", "video analytics", and "intelligent video". No matter how it is referred to, IV turns video into "actionable information," which allows users to receive alerts and make decisions regarding appropriate next steps.
The "intelligence" in IV applications is actually a mathematical analysis of video streams. The data can be used in a multitude of ways, many of which are still under development. The overarching idea is that the surveillance system itself analyzes the video and alerts its operator by triggering an alarm when there is a change to the appropriate level of activity in the field of view. IV is not designed to fully replace human analysis. People will still be needed to assess the entire situation and act accordingly, because human vision is extremely advanced, and is impossible to replicate with mathematical algorithms.
IV can be used in numerous capacities, including object tracking, object counting, license plate recognition, face recognition and object identification. For example, the Boston Police Department has network cameras monitoring the entryway door to their own building. The camera follows each individual as they enter until it gets enough data points for facial recognition. The system then automatically compares this image against an existing database of outstanding arrest warrants. In this way, if someone with an outstanding warrant enters the building for any reason - such as to bail out a friend - the officers know within minutes whether they should detain the person longer.
Offering this sort of intelligence in the video system creates major advantages, the most central of which is the ability to reduce the workload on staff. The IV system is never idle. It is constantly on guard, waiting for an impulse to send an alarm or start recording. There are a number of different ways to set up an IV surveillance system and important factors, like image quality that should be taken in to account.
Surveillance System Architecture with IV
IV can be incorporated into an existing surveillance system, or built into the architecture of a new system. There are two different types of network security architectures that utilize network video. Those two methods are 1) centralized intelligence, in which all intelligence features and algorithms occur in one location, and 2) distributed intelligence, in which the IV functions occur at dispersed points throughout the installation.