H.264 compression (a.k.a. MPEG-4 Part 10) is the de facto standard in IP video surveillance. Without it, HDTV and megapixel quality video wouldn’t be possible. This technology enables manufacturers to improve frame consistency for better efficiency, such as reducing color nuances and improving color fidelity and comparing adjacent images to remove unchanged details between video frames.
Since compression technologies are driven by the consumer electronics world, expect even more efficiency in the near future — namely H.265. Ray Coulombe’s March 2013 Tech Trends column in STE (www.securityinfowatch.com/10878865) points out how H.265 can influence another area some might consider the edge: streaming video to mobile devices in the field.
Storage at the Edge
Video storage at the edge — connecting a camera or encoder to NAS device or using an internal SD card slot — is nothing new. Almost all manufacturers began including SD card slot options by the mid- to late-2000s, but mostly as a redundant storage fail-safe mechanism. However, edge storage hardware came at a premium. Here’s where Moore’s Law left an imprint once again. Only a few years ago a 1GB card cost around $100; today, a 32GB SD card can be found for less than $50, and many IP cameras and video encoders support up to 64GB.
Thus, by the year 2012, the concept of an all-edge storage system was ready. This is where different edge technologies — namely hardware storage and software intelligence — combine to build a decentralized solution where the cameras/encoders act as the recording device. Once installed, not even a computer is required to run these systems, as the VMS runs inside the edge device too.
These edge-recording surveillance solutions are ideal for systems of 16 cameras or less today. They can also be used for temporary installations or areas with limited bandwidth connectivity. And, just as they started, edge recording can of course still act as a failsafe redundant option for larger systems.
As Moore’s Law drives the cost of storage down and storage capacity up, soon we can expect the SDXC (extended capacity) standard to deliver up to and exceeding 2TB of in-camera storage, which could be years’ worth of video inside an IP camera.
The Edge of Genius
When we talk about the future of surveillance, intelligence must take center stage. It’s estimated today that a staggering 99 percent of all recorded surveillance video is deleted before it’s ever seen. Of the one percent of video that is seen by a person, only one percent of that video is viewed live. As the surveillance industry continues to grow and more cameras are installed throughout the world, we are creating even more video channels to monitor and recordings to search.
This is where intelligence plays. Since IP cameras are computers with lenses, they have the ability to use software to improve surveillance efficiency. That means empowering security practitioners, law enforcement personnel and business owners with proactive video alerts.
Like edge storage, video analytics at the edge have been around for quite some time. In 2000, manufacturers introduced video motion detection, the first intelligent algorithm that resided inside a camera. Motion detection is not only used to alert operators to someone or something in the area, but is also an established practice to “record only on motion” and save bandwidth/storage. It was a tremendous first step for IP video intelligence.
Then the analytic and video intelligence market hit a major bump in the road following the Sept. 11 attacks, when the hype and promise surrounding advanced analytics like facial recognition and bag-left-behind came well before the technology was ready. Fortunately for the market, while many users became understandably sour on the success rate of these advanced analytics, effective edge analytics like people counting, cross-line detection and camera tampering alarms emerged from the brief analytic funding utopia.
It also was proof positive that the camera itself can be turned into an intelligent device.
Quality IP cameras and video encoders now set aside a certain amount of memory and CPU cycles dedicated to running applications in-camera. Some manufactures also support open application platforms that allow third-party software developers to write custom apps that can run in-camera — a platform much like a smartphone.