rbertc's profile - activity

http://www.aishack.in/2010/07/tracking-colored-objects-in-opencv/ (C++) http://aravindc.com/2012/12/26/color-tracking-opencv-python-and-my-first-post/ https://bradmontgomery.net/blog/2008/01/24/tracking-a-laser-pointer-with-python-and-opencv/

That first one is a nice C++ tutorial, google around for a better python example. But basically you'll want to convert video frames from RGB color space to HSV color space. Then you can easily threshold the images to show only pixels that fit some desired Hue range.

I apologize, I guess I'm having a hard time understanding exactly what you're looking for. Could you try to provide more information, like what "face detection" you're using? Simply saying "how can i test the face detection in a laptop?" is way too vague.

What environment are you working in? Opencv comes with some xml classifier files, including a few for face detection. Here is an example of how to use them.

Sander, I would also recommend switching over eventually to traincascade. Haartraining is considered an obsolete application, and traincascade offers more features (in particular TBB multithreading and LBP/HOG/HAAR feature detection). For the time being though, here are some links that helped me: http://note.sonots.com/SciSoftware/haartraining.html http://answers.opencv.org/question/4368/traincascade-error-bad-argument-can-not-get-new/ http://stackoverflow.com/questions/16058080/how-to-train-cascade-properly

Also, using a cascade classifier in java is really easy as far as I understand: http://docs.opencv.org/doc/tutorials/introduction/desktop_java/java_dev_intro.html

You could try using hough circles.