X-Git-Url: https://vcs.maemo.org/git/?a=blobdiff_plain;f=docs%2FappPage%2FLKTracker%2FLKTracker.htm;fp=docs%2FappPage%2FLKTracker%2FLKTracker.htm;h=0000000000000000000000000000000000000000;hb=e4c14cdbdf2fe805e79cd96ded236f57e7b89060;hp=12366044239ab94150a65f602d94a3aec87fa5df;hpb=454138ff8a20f6edb9b65a910101403d8b520643;p=opencv diff --git a/docs/appPage/LKTracker/LKTracker.htm b/docs/appPage/LKTracker/LKTracker.htm deleted file mode 100644 index 1236604..0000000 --- a/docs/appPage/LKTracker/LKTracker.htm +++ /dev/null @@ -1,93 +0,0 @@ - - - - Pyramidal Lucas-Kanade Feature Tracker - - - - - - - - - -
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- Pyramidal Lucas-Kanade Feature Tracker -
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Description

- - - This tool lets you compute optical flow based on the Lucas-Kanade - feature tracker in real time. The optical flow computation is - implemented in pyramidal fashion, from coarse to fine resolution. - Consequently, the algorithm can handle large pixel flows, while - keeping a relatively small window of integration, and therefore - achieve high local accuracy (of the order of 0.1 pixel). The tracking - is done by - cvCalcOpticalFlowPyrLK function that implements algorithm, described - in detail in the report - algo_tracking.pdf. - -

LKDemo.exe

- A simple demo of Lucas-Kanade in pyramid (LKpyr) was created as - shown below: This demo assumes you have USB and a USB camera - installed with directShow. If you are running on Microsoft* - Windows* NT 4.0, this demo will only work if you have written your - own video capture source filter. Microsoft Windows 2000 is best - for this and all the rest of the demos.
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Controls

- [1] Start/Stop video capture - toggle.
- [2] Find a set of trackable - points (labeled by green dots) and track them.
- [3] Turn off the video image - and just show the tracked green points from [2].
- [4] Change the size of the - video display window.
- [5] Adjust USB camera - parameters.
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Limitations

- - This is just a simple, "hard coded" demo. We don't allow - you to change the pyramid depth nor allow you to adjust the - tracking parameters nor the thresholds for acceptable points - (minimum eigen value size). We do not monitor the quality of - the tracked points in this demo, thus when a point is occluded, it - often sticks near or on the occluding boundary. We will add user - parameter adjustments and point quality monitoring next rev. -- - ran out of time for this demo, so sorry. - -

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