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Gesture recognition. Using HMMs and size functions. Approach. Combination of HMMs (for dynamics) and size functions (for pose representation). Size functions. Topological representation of contours. Measuring functions. Functions on the contour to which the size function is computed. - PowerPoint PPT Presentation
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Gesture recognition
Using HMMs and size functions
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Approach
Combination of HMMs (for dynamics) and size functions (for pose representation)
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Size functionsTopological representation of contours
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Measuring functions
Functions on the contour to which the size function is computed
real image
measuring function
family of lines
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Feature extraction 1
An edge map is extracted from the image
real image
edge map
… and …
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Feature extraction 2a family of measuring functions is chosen
… the szfc are computed, and their means form the feature vector
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Hidden Markov modelsFinite-state model of gestures as sequences of a small number of poses
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Four-state HMM
Gesture dynamics -> transition matrix A
Object poses -> state-output matrix C
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EM algorithm
feature matrices: collection of feature vectors along time
EM A,C
learning the model’s parameters through EM
two instances of the same gesture
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EM algorithm -> learning the model’s parameters
Learning algorithm
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Gesture classification
…
HMM 1
HMM 2
HMM n
the new sequence is fed to the learnt gesture’s models
they produce a likelihoodthe most likely model is chosen (if above a threshold)