Vectorizing the Kinect real-world coordinate processing algorithm for speed

Question

I recently started working with the Kinect V2 on Linux with pylibfreenect2.

When I first was able to show the depth frame data in a scatter plot I was disappointed to se

Answer 1

This isn't intended to be a complete answer... I just wanted to point out that you are creating a lot of temporary arrays, where you could do more of the operations in-place:

def depthMatrixToPointCloudPos2(z, scale=1000):

    R, C = numpy.indices(z.shape)

    R -= CameraParams['cx'])
    R *= z
    R /= CameraParams['fx'] * scale

    C -= CameraParams['cy']
    C *= z
    C /= CameraParams['fy'] * scale

    return np.column_stack((z.ravel() / scale, R.ravel(), -C.ravel()))

(If I read your code correctly.)

Also, note the data types, which if you are on a 64-bit machine, will be 64-bit by default. Can you get away with smaller types, to cut down on the amount of data to crunch?