title: Kinect Gesture Recognition Theory
body: <p>What are some of the algorithms involved in detecting user gestures based on skeleton movements?  The ones I'm aware of include:</p>
  
  <p>a) Hidden markov models.  You define a number of parameters for the HMM such as hand position, elbow angle, etc. to feed into your HMM.  And then spend some time training the system, tweaking the parameters, until it can recognize your gestures reliably enough.  I believe this is how Wii gestures are generally done.  Good example with the kinect <a href="http://kinecthacks.net/american-sign-language-recognition-using-kinect/" rel="nofollow">here</a>.</p>
  
  <p>b) Connect the dots. If you have a limited vocabulary of gestures, you could set up collision spheres along the path that each hand would normally take.  You could have the gesture fail if they do not follow the path quickly enough.</p>
  
  <p>Both methods would probably require a lot of tweaking to get the success/fail rate the way you want.  I'm wondering if there's other approaches that I'm not aware of and also what the advantages are of each of these.</p>