Re: Motion estimation vs. background subtraction

"Torvald Helmer" <torvald.helmer@xxxxxxxxxxxxx> wrote in
message <frbbrd$k4h$1@xxxxxxxxxxxxxxxxxx>...
I might be asking a lot of silly questions now :)

I just want to make sure I got everything right.

Computing the mean pixel intesity is okay, and thereby
create a new image set as the background.

The sigma on the other hand, I know how to calculate it
for
a set of values, but how to do it for a set of images? Do
I
calculate the std.dev. for a set, in this case with the
size of 10 values, of pixels containing of all pixels
from
position (1,1), and then do the same with a set of pixels
from position (1,2) until position (n,m). And then do a
std.dev. on all of these values again. So in the end I
have
just one value containing the std.dev, or can I do a mean
of all the std.dev values I get from each pixel-position.
Hope you understand what I meant here.


In this application the following attempts to explain what
I mean by the mean and standard deviation images.

If your image frame is say n x m pixels, then you have n x
m mean values and n x m standard deviation values.

You need to visualize a sequence of say 10 frames as an n x
m parallel stream of 10 numbers, So you end up with a mean
image of n x m pixels and a standard deviation image of n x
m pixels, where the pixel of each of these statistical
images is generated from a sequence of 10 numbers.

Hope that helps

Regards

Dave Robinson
.

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