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What are some of the algorithms involved in detecting user gestures based on skeleton movements? The ones I'm aware of include:

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 here.

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.

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.

Bart
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Steve Vermeulen
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  • Were you able to reach what you were searching for ? I'm currently stuck in the same problem, any help would be appreciated. Thanks – Salem Sayed May 24 '11 at 17:25
  • We were able to get by with solution (b). Due to the nature of the project, we already had 3d animations of each gesture, so we wrote an app to generate the 'dots' based on that (in our case we only needed to generate 'dots' from the hand positions). And we would tweak by hand things like the size of the dots, the spacing between each, the time to hold each position, etc. It wasn't perfect but it got the job done for us. – Steve Vermeulen May 25 '11 at 19:40

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Here is Matthew Tang's work on Hand Gesture Recognition. Hope the references in the article also helps. http://www.stanford.edu/class/ee368/Project_11/Reports/Tang_Hand_Gesture_Recognition.pdf

anil
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