title: Feature extraction in 3D gesture recognition for HMM with Kinect data
body: <p>I have a set of <code>3D</code> points mapped onto <code>[0, 1]</code> segments. These points represent simple gestures like circles, waving etc. Now I want to use <code>Hidden Markov Models</code> to recognize my gestures. First step is to extract features for <code>(X, Y, Z)</code> data. I tried to search something useful and found a couple examples: <code>SIFT</code>, <code>SURF</code>, some kind of <code>Fast Fourier Transform</code> etc.</p>
  
  <p>I'm confused which one I should use in my project. I want to recognize gestures using data from Kinect controller, so I don't need to track joints algorithmically.</p>