Multimodal interactions based on body postures
First Claim
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1. A method for multimodal human-machine interaction comprising:
- sensing a body posture of a participant using a camera (605);
evaluating the body posture to determine a posture-based probability of communication modalities from the participant, the posture-based probability being calculated using a processor in a multimedia device (610);
detecting control input through a communication modality from the participant using a sensing device in the multimedia device (615); and
weighting the control input by the posture-based probability (620).
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Abstract
In one example, a method for multimodal human-machine interaction includes sensing a body posture of a participant using a camera (605) and evaluating the body posture to determine a posture-based probability of communication modalities from the participant (610). The method further includes detecting control input through a communication modality from the participant to the multimedia device (615) and weighting the control input by the posture-based probability (620).
28 Citations
15 Claims
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1. A method for multimodal human-machine interaction comprising:
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sensing a body posture of a participant using a camera (605); evaluating the body posture to determine a posture-based probability of communication modalities from the participant, the posture-based probability being calculated using a processor in a multimedia device (610); detecting control input through a communication modality from the participant using a sensing device in the multimedia device (615); and weighting the control input by the posture-based probability (620). - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method for human-machine interaction implemented by a processor in a multimedia device comprising:
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recognizing a participant in a co-present multi-user multimodal human-machine interaction (705) with a multimedia device (200); initializing a skeletal model of the participant (710); tracking a posture of the participant during the multimodal human-machine interaction using the skeletal model (715); evaluating the participant'"'"'s posture to determine a posture-based probability of communication modalities from the participant (720); receiving application state information and evaluating application state information to determine which communication modalities are available (725); receiving application content information and evaluating a probability of a posture of a participant when presented with the application content (730); detecting control input through a communication modality from the participant (735); and weighting the control input by the posture-based probability (740).
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9. A multimedia device comprising:
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a sensing device (220); an application (235) for presenting a multimedia experience to a participant (115); a recognition module (230) for accepting input from the participant through the sensing device (220); a posture analyzer (M3) for outputting a participant posture; a multimodal combiner (225) for evaluating a probability of a communication modality given the participant posture and for weighting input from the participant by the probability of a communication modality. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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Specification