Converting matches from 8-bit 4 channels to 64-bit 1 channel in OpenCV - opencv

Question

I have a vector of Point2f which have color space CV_8UC4 and need to convert them to CV_64F, is the following code correct?
points1.convertTo(points1, CV_64F);
More details:
I am trying to use this function to calculate the essential matrix (rotation/translation) through the 5-point algorithm, instead of using the findFundamentalMath included in OpenCV, which is based on the 8-point algorithm:
https://github.com/prclibo/relative-pose-estimation/blob/master/five-point-nister/five-point.cpp#L69
As you can see it first converts the image to CV_64F. My input image is a CV_8UC4, BGRA image. When I tested the function, both BGRA and greyscale images produce valid matrices from the mathematical point of view, but if I pass a greyscale image instead of color, it takes way more to calculate. Which makes me think I'm not doing something correctly in one of the two cases.
I read around that when the change in color space is not linear (which I suppose is the case when you go from 4 channels to 1 like in this case), you should normalize the intensity value. Is that correct? Which input should I give to this function?
Another note, the function is called like this in my code:
vector<Point2f>imgpts1, imgpts2;
for (vector<DMatch>::const_iterator it = matches.begin(); it!= matches.end(); ++it)
{
imgpts1.push_back(firstViewFeatures.second[it->queryIdx].pt);
imgpts2.push_back(secondViewFeatures.second[it->trainIdx].pt);
}
Mat mask;
Mat E = findEssentialMat(imgpts1, imgpts2, [camera focal], [camera principal_point], CV_RANSAC, 0.999, 1, mask);
The fact I'm not passing a Mat, but a vector of Point2f instead, seems to create no problems, as it compiles and executes properly.
Is it the case I should store the matches in a Mat?

Answer 1

I am no sure do you mean by vector of Point2f in some color space, but if you want to convert vector of points into vector of points of another type you can use any standard C++/STL function like copy(), assign() or insert(). For example:
copy(floatPoints.begin(), floatPoints.end(), doublePoints.begin());
or
doublePoints.insert(doublePoints.end(), floatPoints.begin(), floatPoints.end());

Answer 2

No, it is not. A std::vector<cv::Pointf2f> cannot make use of the OpenCV convertTo function.
I think you really mean that you have a cv::Mat points1 of type CV_8UC4. Note that those are RxCx4 values (being R and C the number of rows and columns), and that in a CV_64F matrix you will have RxC values only. So, you need to be more clear on how you want to transform those values.
You can do points1.convertTo(points1, CV_64FC4) to get a RxCx4 matrix.
Update:
Some remarks after you updated the question:
Note that a vector<cv::Point2f> is a vector of 2D points that is not associated to any particular color space, they are just coordinates in the image axes. So, they represent the same 2D points in a grey, rgb or hsv image. Then, the execution time of findEssentialMat doesn't depend on the image color space. Getting the points may, though.
That said, I think your input for findEssentialMat is ok (the function takes care of the vectors and convert them into their internal representation). In this cases, it is very useful to draw the points in your image to debug the code.