Human interface device and method
First Claim
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1. A method for state tracking based gesture recognition engine for a sensor system comprising the steps of:
- defining a plurality of sequential states of a finite-state machine, wherein the finite state machine is an N-state Hidden Markov Model (HMM) comprising a state transition probability matrix,determining a Sequence Progress Level (SPL) for each state,mapping a state probability distribution to an SPL on run-time, andutilizing the mapped SPL estimate as an output value of the sensor system, wherein a most likely state and/or a most likely state sequence is computed using a Viterbi Algorithm,wherein for each discrete-time instance the data provided by the sensor system is forwarded to the finite state machine which computes a state probability distribution for the N-state HMM, and wherein, for each discrete-time instance, a state with the maximum probability is selected and an SPL associated with the state is output.
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Abstract
A method for state tracking based gesture recognition engine for a sensor system has the steps of: defining a plurality of sequential states of a finite-state machine, determining a Sequence Progress Level (SPL) for each state, mapping a state probability distribution to a (single) SPL on run-time, and utilizing the mapped SPL estimate as an output value of the sensor system.
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29 Claims
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1. A method for state tracking based gesture recognition engine for a sensor system comprising the steps of:
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defining a plurality of sequential states of a finite-state machine, wherein the finite state machine is an N-state Hidden Markov Model (HMM) comprising a state transition probability matrix, determining a Sequence Progress Level (SPL) for each state, mapping a state probability distribution to an SPL on run-time, and utilizing the mapped SPL estimate as an output value of the sensor system, wherein a most likely state and/or a most likely state sequence is computed using a Viterbi Algorithm, wherein for each discrete-time instance the data provided by the sensor system is forwarded to the finite state machine which computes a state probability distribution for the N-state HMM, and wherein, for each discrete-time instance, a state with the maximum probability is selected and an SPL associated with the state is output. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29)
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