CODEWITHSUNDEEP
machine-learningclassificationgesture-recognitionpattern-recognitionhidden-markov-models
user5692502
user5692502

Reputation: 63

continuous gesture recognition using Hidden Markov Model

When we need to do gesture recognition, we should train several HMMs for each gesture. then when we need to classify the gesture we compute the sequence probability from each HMM and take the one with the highest likelihood

But what to do when we need to classify multiple gestures in a sequence and we don't know how to segment the multiple gestures to take the same approach with single gesture

So how can we do this sequence classification? is HMM appropriate? are there other ways?

Thanks

Upvotes: 4

Views: 351

Answers (1)

Prune
Prune

Reputation: 77880

NLP generally does this with real-time interpretation. Set a match threshold; when a sequence of motions resolves to a unique gesture and meets the threshold, you interpret that as a gesture.

This is simple in description. In practice, there is a lot of feedback, especially if some gestures are subsets of others, or if the matches are not quite as crisp as we'd like.

If you want to use HMM, can you seed it after some training with markers for terminal states?

Upvotes: 3

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