Summary
So basically you have a Wii remote that takes {x,y,z} position every so often and generates a sequence of these positions. A hidden Markov model is trained on sequences and then used to classify a gesture (model with max Viterbi probability). As you increase number of HMM states and number of training examples, accuracy increases. Without user specific data, you get around 50% accuracy regardless. As you increase number of states, your system slows down.
Discussion
The application is neat, but all their results are of the "Duh" type. The game is neater than the implementation details, since you can combine spells and stuff for different effects.
How do they do segmentation?
1 comment:
"How do they do segmentation?"
Magiic.
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