AROUSAL STATE CLASSIFICATION MODEL GENERATING DEVICE, AROUSAL STATE CLASSIFYING DEVICE, AND WARNING DEVICE
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Abstract
There is provided an arousal state classification model generating device for generating a blink waveform pattern model and an arousal state pattern model based on data on a blink waveform, which are preferably used for accurately estimating an arousal level with respect to unspecified object persons, an arousal state classifying device for classifying the arousal state of an object person, and a warning device. In the arousal state classification model generating device, a first pattern model is generated by learning a statistical model by using as learning data first feature data extracted from the blink data of at least one of the eyes of each object person at the time of blinking and blink waveform identification information. A second pattern model is generated by learning a statistical model by using as learning data second feature data including data on the occurrence ratio of each specific type of blink waveform in the sequence of analysis intervals and arousal state information data in which arousal state information indicating the arousal state of each object person is provided to each sequence of analysis intervals.
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Citations
44 Claims
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1-23. -23. (canceled)
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24. An arousal state classification model generating device for generating a statistical model to determine an arousal state of an object person, the arousal state classification model generating device characterized by comprising:
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learning data storage means for storing first feature data extracted from blink data of at least one eye of each object person at the time of blinking, and blink waveform identification information data in which blink waveform identification information indicating a specific type of blink waveform is provided to each blink in the blink data; blink waveform pattern model generation means for learning a statistical model by using as learning data the first feature data and the blink waveform identification information data stored in the learning data storage means, and generating a first pattern model having as an input the first feature data and having as an output a likelihood for the blink waveform identification information in relation to the first feature data; feature data generation means for generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms in an analysis interval based on the blink waveform identification information data stored in the learning data storage means; and arousal state pattern model generation means for learning a statistical model by using as learning data the second feature data generated by the feature data generation means and arousal state information data in which arousal state information indicating the arousal state of the object person is provided to each sequence of the analysis intervals, and generating a second pattern model having as an input the second feature data and having as an output a likelihood for the arousal state information in relation to the second feature data. - View Dependent Claims (25, 26, 27, 28, 29, 30, 31, 32, 33, 34)
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35. An arousal state classification model generating method for generating a statistical model to determine an arousal state of an object person, the arousal state classification model generating method characterized by comprising:
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a learning data storage step of storing first feature data extracted from blink data of at least one eye of each object person at the time of blinking, and blink waveform identification information data in which blink waveform identification information indicating a specific type of blink waveform is provided to each blink in the blink data; a blink waveform pattern model generation step of learning a statistical model by using as learning data the first feature data and the blink waveform identification information data stored in the learning data storage step, and generating a first pattern model having as an input the first feature data and having as an output a likelihood for the blink waveform identification information in relation to the first feature data; a feature data generation step of generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms in an analysis interval based on the blink waveform identification information data stored in the learning data storage step; and an arousal state pattern model generation step of learning a statistical model by using as learning data the second feature data generated in the feature data generation step and arousal state information data in which arousal state information indicating the arousal state of the object person is provided to each sequence of the analysis intervals, and generating a second pattern model having as an input the second feature data and having as an output a likelihood for the arousal state information in relation to the second feature data. - View Dependent Claims (36, 37, 38, 39)
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40. An arousal state classification model generating program for generating a statistical model to determine an arousal state of an object person, causing a computer to function as:
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a learning data storage means for storing first feature data extracted from blink data of at least one eye of each object person at the time of blinking, and blink waveform identification information data in which blink waveform identification information indicating a specific type of blink waveform is provided to each blink in the blink data; blink waveform pattern model generation means for learning a statistical model by using as learning data the first feature data and the blink waveform identification information data stored in the learning data storage means, and generating a first pattern model having as an input the first feature data and having as an output a likelihood for the blink waveform identification information in relation to the first feature data; feature data generation means for generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms an analysis intervals based on the blink waveform identification information data stored by the learning data storage means; and arousal state pattern model generation means for learning a statistical model by using as learning data the second feature data generated by the feature data generation means and arousal state information data in which arousal state information indicating the arousal state of the object person is provided to each of the sequences of analysis intervals, and generating a second pattern model having as an input the second feature data and having as an output a likelihood for the arousal state information in relation to the second feature data. - View Dependent Claims (41, 42, 43, 44)
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Specification