OpenCV, C++: Distance between two points

Question

For a group project, we are attempting to make a game, where functions are executed whenever a player forms a set of specific hand gestures in front of a camera. To process the images, we are using Open-CV 2.3.

During the image-processing we are trying to find the length between two points. We already know this can be done very easily with Pythagoras law, though it is known that Pythagoras law requires much computer power, and we wish to do this as low-resource as possible.

We wish to know if there exist any build-in function within Open-CV or standard library for C++, which can handle low-resource calculations of the distance between two points. We have the coordinates for the points, which are in pixel values (Of course).

Extra info: Previous experience have taught us, that OpenCV and other libraries are heavily optimized. As an example, we attempted to change the RGB values of the live image feed from the camera with a for loop, going through each pixel. This provided with a low frame-rate output. Instead we decided to use an Open-CV build-in function instead, which instead gave us a high frame-rate output.

Answer 1

You should try this

cv::Point a(1, 3);
cv::Point b(5, 6);
double res = cv::norm(a-b);//Euclidian distance

Answer 2

As you correctly pointed out, there's an OpenCV function that does some of your work :)

(Also check the other way)

It is called magnitude() and it calculates the distance for you. And if you have a vector of more than 4 vectors to calculate distances, it will use SSE (i think) to make it faster.

Now, the problem is that it only calculate the square of the powers, and you have to do by hand differences. (check the documentation). But if you do them also using OpenCV functions it should be fast.

Mat pts1(nPts, 1, CV_8UC2), pts2(nPts, 1, CV_8UC2);
// populate them
Mat diffPts = pts1-pts2;
Mat ptsx, ptsy;
// split your points in x and y vectors. maybe separate them from start
Mat dist;
magnitude(ptsx, ptsy, dist); // voila!

The other way is to use a very fast sqrt:

// 15 times faster than the classical float sqrt. 
// Reasonably accurate up to root(32500)
// Source: http://supp.iar.com/FilesPublic/SUPPORT/000419/AN-G-002.pdf

unsigned int root(unsigned int x){
    unsigned int a,b;
    b     = x;
    a = x = 0x3f;
    x     = b/x;
    a = x = (x+a)>>1;
    x     = b/x;
    a = x = (x+a)>>1;
    x     = b/x;
    x     = (x+a)>>1;
    return(x);  
}