OpenCV looks much more heavyweight than what you need, but may be useful in prototyping.<br><br>Phase correlation looks for the translational offset of an entire image between two frames. It is also probably much more heaviweight than what you need. In the end the result you get will be pretty similar to that obtained by the centroid method. You will only get higher than single-pixel precision with phase correlation if you do subpixel extremum detection anyway, and you can do that directly in image space, saving a lot of computation.
<br><br><br><div><span class="gmail_quote">On 9/6/07, <b class="gmail_sendername"><a href="mailto:linaccess@yokoy.de">linaccess@yokoy.de</a></b> <<a href="mailto:linaccess@yokoy.de">linaccess@yokoy.de</a>> wrote:</span>
<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">hi,<br><br>has anybody experince (and libs) with phase correlation?<br>I have no idea how to implement it.
<br><br>Another promising lib is<br><a href="http://en.wikipedia.org/wiki/OpenCV">http://en.wikipedia.org/wiki/OpenCV</a><br><br>greeting,<br>yokoy<br><br><br><br>On Wed, 05 Sep 2007 19:40:29 -0400<br>"Benjamin M. Schwartz" <
<a href="mailto:bmschwar@fas.harvard.edu">bmschwar@fas.harvard.edu</a>> wrote:<br><br>> -----BEGIN PGP SIGNED MESSAGE-----<br>> Hash: SHA1<br>><br>> I am not at all clear on what you are doing, or why. However, you may want to
<br>> check out<br>><br>> <a href="http://en.wikipedia.org/wiki/Phase_correlation">http://en.wikipedia.org/wiki/Phase_correlation</a><br>><br>> this is the most accurate possible method for recovering the position of a
<br>> moving object. If you have a fast FFT available it may be quite efficient.<br>><br>....<br>_______________________________________________<br>Devel mailing list<br><a href="mailto:Devel@lists.laptop.org">Devel@lists.laptop.org
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