[bArray]

> Well, they are having to align some number of sensors

> ensuring sufficient overlap to ensure that they can

> process the images together.

It would be much easier to avoid the issue of stitching altogether and simply process the images separately, then merge the resulting output data. As far as I'm aware, you're not going to find a GPU that can process a 500MP image efficiently.

[starky]

But when the images are processed separately, your required actual recorded resolution could go up quickly as your overlap between imagers needs to ensure that a face to be identified is contained within a single imager, or at least a large enough portion of the face is contained within an imager to give a sufficiently high confidence of being correct. So as I mentioned, this becomes even more storage intensive, though because there is less image processing, it becomes more CPU efficient.

[bArray]

I disagree, if you miss an individual on the first capture, there's always the second capture. The number of people you fail to detect because their face is halfway between two screens would likely be far exceeded by the number of faces you fail to detect because there's an issue within the algorithm itself or simply the face isn't fully visible.

That's okay. There are of course limitations. You can't detect faces you can't see, for example (i.e. somebody walking the wrong direction). If you're detecting 10k faces at an accuracy of 99.99%, one in every detection frame is a failure.