Now let us consider a 3 channel image with \texttt{bgr} color ordering (the default format returned by imread):
\begin{lstlisting}
Scalar intensity = img.at<uchar>(x, y);
Vec3b intensity = img.at<Vec3b>(x, y);
uchar blue = intensity.val[0];
uchar green = intensity.val[1];
uchar red = intensity.val[2];
\end{lstlisting}
You can use the same method for floating-point images (for example, you can get such an image by running Sobel on a 3 channel image):
\begin{lstlisting}
Vec3f intensity = img.at<Vec3f>(x, y);
float blue = intensity.val[0];
float green = intensity.val[1];
float red = intensity.val[2];
\end{lstlisting}
The same method can be used to change pixel intensities:
\begin{lstlisting}
img.at<uchar>(x, y) = 128;
\end{lstlisting}
There are functions in OpenCV, especially from calib3d module, such as \texttt{projectPoints}, that take an array of 2D or 3D points in the form of \texttt{Mat}. Matrix should contain exactly one column, each row corresponds to a point, matrix type should be 32FC2 or 32FC3 correspondingly. Such a matrix can be easily constructed from std::vector:
\begin{lstlisting}
vector<Point2f> points;
//... fill the array
Mat _points = Mat(points);
\end{lstlisting}
One can access a point in this matrix using the same method \texttt{Mat::at}: