From d1b923bee9f6809e0cf1ca21d20b66ea49db495e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jonathan=20D=C3=B6nszelmann?= Date: Sat, 11 Dec 2021 08:03:10 +0100 Subject: [PATCH] Update name from Gunner to Gunnar as that's the name he published his paper under. --- .../js_video/js_lucas_kanade/js_lucas_kanade.markdown | 4 ++-- doc/tutorials/video/optical_flow/optical_flow.markdown | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/doc/js_tutorials/js_video/js_lucas_kanade/js_lucas_kanade.markdown b/doc/js_tutorials/js_video/js_lucas_kanade/js_lucas_kanade.markdown index a86bf11223..f4e4f231b0 100644 --- a/doc/js_tutorials/js_video/js_lucas_kanade/js_lucas_kanade.markdown +++ b/doc/js_tutorials/js_video/js_lucas_kanade/js_lucas_kanade.markdown @@ -133,9 +133,9 @@ Dense Optical Flow in OpenCV.js Lucas-Kanade method computes optical flow for a sparse feature set (in our example, corners detected using Shi-Tomasi algorithm). OpenCV.js provides another algorithm to find the dense optical flow. It -computes the optical flow for all the points in the frame. It is based on Gunner Farneback's +computes the optical flow for all the points in the frame. It is based on Gunnar Farneback's algorithm which is explained in "Two-Frame Motion Estimation Based on Polynomial Expansion" by -Gunner Farneback in 2003. +Gunnar Farneback in 2003. We use the function: **cv.calcOpticalFlowFarneback (prev, next, flow, pyrScale, levels, winsize, iterations, polyN, polySigma, flags)** diff --git a/doc/tutorials/video/optical_flow/optical_flow.markdown b/doc/tutorials/video/optical_flow/optical_flow.markdown index 45bbfa46ce..a9faf9be13 100644 --- a/doc/tutorials/video/optical_flow/optical_flow.markdown +++ b/doc/tutorials/video/optical_flow/optical_flow.markdown @@ -136,9 +136,9 @@ Dense Optical Flow in OpenCV Lucas-Kanade method computes optical flow for a sparse feature set (in our example, corners detected using Shi-Tomasi algorithm). OpenCV provides another algorithm to find the dense optical flow. It -computes the optical flow for all the points in the frame. It is based on Gunner Farneback's +computes the optical flow for all the points in the frame. It is based on Gunnar Farneback's algorithm which is explained in "Two-Frame Motion Estimation Based on Polynomial Expansion" by -Gunner Farneback in 2003. +Gunnar Farneback in 2003. Below sample shows how to find the dense optical flow using above algorithm. We get a 2-channel array with optical flow vectors, \f$(u,v)\f$. We find their magnitude and direction. We color code the -- GitLab