We put on the first demonstration of true megapixel analytics in the industry at our ISC West booth last week.

It was eye-catching. Lots of people stood there staring at the analytics detecting people, cars, trucks, motorcycles, sailboats, speedboats, etc. Here’s a picture:

Unfortunately, this blog can’t show the full resolution or video, which you really need to see to appreciate how incredible it looks.

When I say this is the first public display of “true megapixel analytics” I mean the resolution being analyzed is megapixel. There have been cameras with megapixel video that have had analytics processing before. CoVi is a good example, may they rest in peace. They sold a 1 MP camera that ran ObjectVideo analytics. However, the resolution of the analytics was only CIF (320 x 240 pixels), which gave hardly any detection range. It was silly to put CIF analytics on a megapixel camera.

Why hasn’t anyone ever demonstrated megapixel analytics before? Because of the sheer processing power that other technologies need to do this.

VideoIQ’s technology is different. We need about 1/8th the amount of processing power compared to other high quality analytics systems. So, we can run the whole thing in one of the popular low cost DSP processors. But all other analytics technologies need a lot more horsepower.

For example, ObjectVideo on their web site claims they can run up to 4CIF resolution video in the same DSP chip we are using. However, in most cases the users of OV onboard are only running CIF resolution, because there are serious limitations running 4CIF, such as only being able to have one rule running at a time and a limited number of objects that can be detected.

IOimage uses two DSP processors in their cameras to get high quality and avoid compromising detection.

The camera we demonstrated was a 1080p camera, which is 1920 x 1080 pixels. We demonstrated it live at the show, with the analytics all running in the camera. It provides 3X the horizontal coverage of a standard resolution camera, and more than 2X the anaytics detection distance.

For other technologies to run 1080p analytics, they would need more than 6 times as much processing power, compared to 4CIF video. That would mean 6 DSP chips, or some very expensive high end DSP chips.

If you try to run this on a server or a PC, you would need a full dual core processor to run one camera. So, you can see why it’s never been shown before. It is impractical for other technologies.

The other industry first we showed is something we call IQTrack. It uses the video analytics to automatically track and zoom on objects in the field of view. Here’s a picture:

This is different from PTZ camera tracking. If you look at the lower left of the picture, you will see that the whole field of view is still being recorded and it shows where in the scene you are zoomed into. So, you can always go back later and pick another part of the video to look into.

The other unique thing is, if many people are in the area, you can click on one person and it will zoom in on and track just that one person. That’s never been shown before either.

Watching it, you can immediately see that there is no comparison between watching video that is automatically zooming and tracking on important objects, versus static video cameras. It pulls your eyes to exactly what is important. I think this is going to be very popular for megapixel cameras.

The 1080p cameras we sold will also be the first cameras to ship with a new imager from Sony that has some amazing low light performance. We are still testing it, but it looks to be 2X-4X better than any other multi-megapixel imagers used in the security industry.

And of course, the camera we showed included a hard drive so that you can store 1-2 months of high quality 1080p video. This solves the bandwidth problem for megapixel cameras, since it needs no bandwidth to record, and eliminates the need for external storage in most cases.

Now that true megapixel analytics have arrived, I think it is going to set the standard, and I think it offers incredible visual value to megapixel cameras, even if you don’t want the analytics for detecting alarms.