The definition of covariance is
Cov(x, y) = E[ (X-E(X)) * (Y-E[Y]) ]
where E is abbreviation of expectation. It is same with Mean.
so..
X = [1 2 3 4 5];
E(X) -> 3 or 3.75
3 is the result of "sum(X)/5"
3.75 is the result of "sum(X)/(5-1)"
In the statistics, mean is divided by N-1 to avoid outlier data affection.
*Example of Covariance
X = [ 2 3 4 2 1 4]
Y = [ 2 4 2 1 6 8]
meanX = sum(X) / 6 -> 2.667
(X - meanX) -> [-0.6667 0.3333 1.3333 -0.6667 -1.6667 1.3333]
(X - meanX) * (X -meanX) -> [ 0.4444 0.1111 1.7778 0.4444 2.7778 1.7778]
cov(x, x) -> sum( ( (X - meanX) * (X -meanX) ) ) / (N-1)
-> 1.4667
cov of X, Y is like that
-> cov(x,x) cov(x,y)
cov(x,y) cov(y,y)
-> 1.4667 0.5333
0.5333 7.3667
in the matlab...
2/15/2013
Subscribe to:
Post Comments (Atom)
-
As you can see in the following video, I created a class that stitching n cameras in real time. https://www.youtube.com/user/feelmare/sear...
-
I use MOG2 algorithm to background subtraction. The process is resize to small for more fast processing to blur for avoid noise affectio...
-
Created Date : 2011.10 Language : C/C++ Tool : Microsoft Visual C++ 2008 Library & Utilized : OpenCV 2.3 Reference : SIFT referenc...
-
Created Date : 2009.10. Language : C++ Tool : Visual Studio C++ 2008 Library & Utilized : Point Grey-FlyCapture, Triclops, OpenCV...
-
After training SVM, we should test the trained XML data is reliable or not.. The method to extract HOG feature is refer to -> http://fe...
-
RTSP(Real Time Streaming Protocol) is video streaming, it usually sent from network camera. VideoCapture function in opencv also can get r...
-
* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm...
-
OpenCV has AdaBoost algorithm function. And gpu version also is provided. For using detection, we prepare the trained xml file. Although...
-
This is example of SVM learning method. This example is I already have explained in past time. See the this page - > http://feelmare.bl...
-
fig 1. Left: set 4 points (Left Top, Right Top, Right Bottom, Left Bottom), right:warped image to (0,0) (300,0), (300,300), (0,300) Fi...
No comments:
Post a Comment