Machine learning rocks!

Quite a weekend of work for Jin...

The HMM will be good since we can use the log-likelyhood as a scoring method similar to the path cost on the DTW. Also, your setup of the 27-way transitions is clever and will make for good report material.

As far as smoothing goes... we can use a low-pass filter and then calculate the difference, which is what Jin's first idea is.

My other idea is something along the lines of:

0. Perhaps normalize the length of the sequence (I need to think about this step more, could probably use the DTW to warp all of the sequences of an action to a common length)
1. Take a DFT or DCT of the sequences.
2. Average the DCTs together and normalize
3. Find the peak (mode) of the averaged DFT
4. Find the ratio of energy above and below the mode.
5. Perform the same math on a exercise example and compare the energy above the mode.

Another idea:

Use a more and more severe smoothing filter until the DTW scores changes drastically (say 20%?) (or the HMM log-likely hood). Then do the comparison as Jin suggested.