|
Hello, good evening. I am just starting learn about Hidden Markov Model to recognize motion picture. Assume in one frame I have m-dimension feature. I want to ask, how to represent the sequence of data (which every frame has m-dimension feature) into the State Transition matrix and Emission matrix ? How many hidden state (S_1, S_2, S_h) that I need ? I am trying to Google it but I didn't find it. It would be nice if someone can give the example too. Thanks :) Update : Ilustration :
Assume that one is for getting Probability for motion "A". And I have another model for motion "B". |
|
I am not sure if I understand you. It would probably be better if you explain what the features are and what you are trying to do. I think your features are "tags" ie x , rather than the state "s"... if so then worth looking at this lecture http://www.cs.columbia.edu/~mcollins/loglinear.pdf othewise if your m-dimensional feature is a state, then yes each (live) m dimensional feature combination is turned into a single tagged state [and you have a dictionary of states, state transitions ], so ecevything is the same michael collins coursera lecture notes http://www.cs.columbia.edu/~mcollins/ explain and give peseudo code for hmms hey, I tried to illustrate my model and update the question. Can you correct me if I do it wrong ?
(Jul 11 '13 at 00:14)
psuedobot
|
|
HMMs are most frequently presented using a categorical distribution for p(x|s) (the emission probabilities) since this case is relatively easy to understand and what you would use when working with text. However there is no reason you can't use a more appropriate distribution here, like an m-dimensional Gaussian. Obviously you would need to also make the appropriate change to the way you calculate p(x|s) and update the emission probability parameters, but everything else remains mostly the same. so I must put my m-dimesional feature into 1 dimensional feature so I can present it into the state ? also do you have any good resource to learn about HMM, I would like to try implement the HMM by hand so I can understand it better
(Jul 09 '13 at 14:44)
psuedobot
|
