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I am new to statistical pattern recognition and trying to learn.To begin with I am trying to work with two class problems and trying to classify motion activities as mentioned in the paper "Object Trajectory-Based Activity Classification and Recognition using Hidden Markov Models". In this paper, the authors have used GMM for estimating the PDF for each motion pattern class. But I have several doubts and shall be grateful for the following answers

  1. If there are 5 experimental data with 4 feature vectors(4 columns of data) of length 1000 samples/rows for each of the two classes(say,running and walking) then is the pdf from Gaussian mixture model obtained for each of the 5 experimental data or only for each class? If it is for each class, then how is it done? I really do not know and please pardon if this sounds too trivial.
  2. Is it always necessary to find the pdf of the data before classification task in general? Does the pdf control in deciding which model based approach to choose for classification purpose?
  3. Are there any such model based approaches for classification?
  4. As far as my understanding goes, GMM is a clustering algorithm like k-means. So, are there other ways other than using Hidden Markov Model (I want to avoid HMM due to further complexities in understanding it) for classification with GMM?
  5. Can GMM be combined with regression models like AR,MA,ARMA for model based classification? If so, then pointers to resources which explain this shall be helpful.
  6. Is there a Matlab implementation of multivariate GMM for the said application of classification?

Thank you in advance.

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  • $\begingroup$ search for gmdistribution, fit, and cluster. $\endgroup$ – EngrStudent Jul 7 '13 at 20:47
  • $\begingroup$ See Professor Bozdogan's work on these problems who really the first to study these problems on mixture models dating back to 1981. Since then such problems have become very popular in statistical literature and in many applications. $\endgroup$ – user37974 Jan 26 '14 at 20:03
  • $\begingroup$ Welcome to the site, @Esra. This isn't really an answer to the OP's question. It is more of a comment. Please only use the "Your Answer" field to provide answers. I recognize it's frustrating, but you will be able to comment anywhere when your reputation >50. Alternatively, you could try to expand it to make it more of an answer. Since you are new here, you may want to read our tour page, which contains information for new users. $\endgroup$ – gung Jan 26 '14 at 20:06

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