Height is easy. You know that the camera is at $(0,0,0)$. Just fit a plane to the ground pixels and measure the orthogonal distance from the origin to this plane.
Frame rate is more of an issue. It is correlated with the speed of the user moving the camera. I suppose an approach would be to actually take the Kinect camera, move it like a normal person does and record the frame rate. You could then compute the optical flow in your dataset and record the magnitudes of flow vectors. You could then train a classifier (e.g. random forest) to learn to regress the frame rate given the flow vectors. Assuming that the camera motion is very similar, you could then put your dataset into this classifier and regress the frame rates for the whole trajectory. The average over all sets of frames should give you, kind of, the frame rate.