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about CamShiftTracker (FreeFrame DShow9)

open source

• code available via:https://github.com/vvvv/vvvv-sdk/tree/develop/vvvv45/src/nodes/freeframes/CamShiftTracker
• includes project files for the Code::Blocks c++ IDE
• depends on opencv 1.0 libraries

usage

When you use CamShiftTracker the most important step is the fine tuning of the tracking parameters.

These are:

• Size and orientation of initial ROI
• Saturation min, Value min and max

To achieve an optimal tracking output, these parameters have to be adjusted to the lighting situation of the video scene (or vice versa).

If possible, turn off automatic gain control (AGC), automatic brighness ajustment etc. on your camera.

During fine tuning of the parameters you should have Show Backproject set to 1, so you can see which pixels of the image are considered as belonging to the object (i.e. those which are white). Also, set Show ROI to 1, to see the search frame.
When nearly all pixels in the area of the object are white and the rest of the image is black, you're done.

Like a good linear minimizer, adjust one parameter at a time, then continue with the next one. Playing around will give you a feeling for this...

Be sure that your object lies in or, ideally, fills the initial ROI when you initialise the tracker by banging Init Tracker. You will get the best results by using a white background. Since white (background) pixels have a very low saturation, you can kick 'em out by increasing the 'Saturation min' pin value.
Adjust Value min and Value max to the range of your object brightness:

After each tuning step, init Tracker again to submit the tracking values and refine the object search.

If all that doesn't help, you might have to improve the lighting situation.
Think about illuminating the object with a lamp, or adding a diffuser if the video image is too dark and the colors don't come out right.