If you’re switching from an old analog CCTV system to a new IP video surveillance system, it’s important to ensure the system is properly designed. And while some aspects such as bandwidth, processor throughput, and storage are frequently factored into IP video design, others are either not considered or applied incorrectly, which can result in excessive storage requirements and operating costs. Learn about some of the lesser known components of effective IP video design in our blog.
IP Video Design
What are some of the problems with IP video design?
The main problem with many IP video design strategies is that they don’t take all necessary factors into consideration, or they’re not applied the right way. For example, many designers calculate the bandwidth and storage needs for the system using resolution and frame rates. The higher the resolution and frame rates, the higher the image quality. However, many cameras are observing situations that do not require such a high frame rate. The result is a larger server than necessary, and the double payment for more storage space, and higher operating costs for a larger server.
Cameras that are intended to specifically identify persons or license plates, will require the highest level of resolution. But if a camera is needed only to classify objects in a scene, the resolution requirements drop by half. Cameras that only need to gather general information such as traffic flow require about one-eighth the resolution of identification cameras.
To calculate the resolution needed, “Measure the width of the subject field at the required distance. Multiply the width by the pixels per for required and you’ll have the number of pixels required to capture the scene.” In addition, “Remember that doubling the pixel count can double bandwidth and storage but will only increase resolution by 50 percent.”
Lens selection is another important component of IP video design. Low-quality lenses are fine for general information cameras, but will not work for identification purposes, as they can’t focus to the necessary resolution. Depth of field is another important consideration in situations where a camera has a wide viewing area.
Lots of designers opt for higher frame rates, but because of the way MPEG and H.264 algorithms encode video, higher frame rates don’t actually result in more information. This is because they encode based on differences from scene to scene. So actually, “As the frame rate increases, the difference from one scene to the next reduces, and therefore less data is in the stream.”
But, because every frame needs to be recreated at the viewing station, higher frame rates force processors to work faster. And because many viewing scenes don’t contain much information, frame rate can be reduced without affecting the quality of the stream.
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