CPU vs GPU

I think some of the incumbents are going in the wrong direction, while I am a little envious of some that I think got it 100% right.

In the old days, things were simple and cameras were really dumb, but today cameras are often quite clever, but now hordes of VMS salespeople are now trying to make them dumb again, thereby driving the whole industry backward to the detriment of the end-users. Eventually, though, I think people will wake up and realize what’s going on.

The truth is that you can run a VMS on a $100 hardware platform (excluding storage). Yet,  if you are keeping up on the latest news, it seems that you that you need a $3000 monster PC with a high-end GPU to drive it. In the grand scheme of things (cost of cameras, cabling and VMS licenses) the $2900 dollar difference is peanuts, but it bothers me nonetheless. It bothers me because it suggests a piss-poor use of the available resources.

pi

A $40 VMS capable PC

As I have stated quite a few times, the best way to detect motion is to use a PIR sensor, but if you insist on doing any sort of image analysis the best way to do it is on the camera. The camera has access to the uncompressed frame in it’s most optimal format, and it brings its own CPU resources to the party.  If you move the motion detection to the camera, then your $100 platform will never have to decode a single video frame, and can focus on what the VMS should be doing: reading, storing and relaying data.

In contrast, you can let the camera throw away a whole bunch of information as it compresses the frame. Then send the frame across the network (dropping a few packets for good measure) to a PC that is sweating bullets as it must now decompress each and every frame since MPEG formats are all or (almost) nothing formats, there is no “decode every 4th frame” option here. The decompressed frame now contains compression artifacts which contribute to making accurate analysis difficult. The transmission of the frames across the network can also lead to the frames not arriving at a steady pace, which causes other problems for video analytics engines.

missing_packets

Look at all that motion! Let’s sound the alarm.

VMS vendors now say they have a “solution” to the PC getting crushed under the insane workload required to do any sort of meaningful video analysis. Move everything to a GPU they say – and it’s kinda true. If you bring up the task manager in windows, your CPU utilization will now be lower, but crank up GPU-z and you (should) see the GPU buckling under the load. One might ask if it would not have been cheaper to get a $350 octa-core Ryzen CPU instead of a $500 GPU

gpu-z-3

Some will say that if the integrator has to spend 2 days setting up the cameras using edge detection, it might be cheaper if they just spring for the super PC and do everything on that. This assumes that the setup can actually be done quicker than when setting it up on a camera. I’d wager that a lot of motion detection systems are not really necessary, and in other cases, the VMS motion detection is simply not as good as the edge-based detection, which in some tragic instances completely invalidate the system and renders it worthless as people and objects magically teleport from one frame to the next.

 

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