From e98da758ccb329215933e8b3c926d46537f0fe1e Mon Sep 17 00:00:00 2001 From: matech96 Date: Thu, 10 May 2018 22:07:50 +0200 Subject: [PATCH] Update py_meanshift.markdown Fix publication date of "Computer Vision Face Tracking for Use in a Perceptual User Interface" from 1988 to 1998. --- doc/py_tutorials/py_video/py_meanshift/py_meanshift.markdown | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/py_tutorials/py_video/py_meanshift/py_meanshift.markdown b/doc/py_tutorials/py_video/py_meanshift/py_meanshift.markdown index 8976cc3..b246d76 100644 --- a/doc/py_tutorials/py_video/py_meanshift/py_meanshift.markdown +++ b/doc/py_tutorials/py_video/py_meanshift/py_meanshift.markdown @@ -101,7 +101,7 @@ Did you closely watch the last result? There is a problem. Our window always has car is farther away and it is very close to camera. That is not good. We need to adapt the window size with size and rotation of the target. Once again, the solution came from "OpenCV Labs" and it is called CAMshift (Continuously Adaptive Meanshift) published by Gary Bradsky in his paper -"Computer Vision Face Tracking for Use in a Perceptual User Interface" in 1988. +"Computer Vision Face Tracking for Use in a Perceptual User Interface" in 1998. It applies meanshift first. Once meanshift converges, it updates the size of the window as, \f$s = 2 \times \sqrt{\frac{M_{00}}{256}}\f$. It also calculates the orientation of best fitting ellipse -- 2.7.4