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 8976cc3f7c..b246d76067 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