Scenario-specific body-part tracking
First Claim
1. A method of retraining a general-purpose body-part tracker, the method comprising:
- receiving a set of different instances of scenario data, each instance of scenario data representing a human training-subject performing an action specific to a particular scenario;
iterating over the set of different instances of scenario data with the general-purpose body-part tracker, the general-purpose body-part tracker previously trained using supervised machine learning to identify one or more general-purpose parameters to be used by the general-purpose body-part tracker to track a human subject; and
identifying one or more special-purpose parameters to be selectively used to augment or replace the one or more general-purpose parameters if the general-purpose body-part tracker is used to track a human subject performing the action specific to the particular scenario; and
associating the one or more special-purpose parameters with a scenario identifier that identifies the particular scenario for which the special-purpose parameters are to be selectively used by the general-purpose body-part tracker to track a human subject.
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Accused Products
Abstract
A human subject is tracked within a scene of an observed depth image supplied to a general-purpose body-part tracker. The general-purpose body-part tracker is retrained for a specific scenario. The general-purpose body-part tracker was previously trained using supervised machine learning to identify one or more general-purpose parameters to be used by the general-purpose body-part tracker to track a human subject. During a retraining phase, scenario data is received that represents a human training-subject performing an action specific to a particular scenario. One or more special-purpose parameters are identified from the processed scenario data. The special-purpose parameters are selectively used to augment or replace one or more general-purpose parameters if the general-purpose body-part tracker is used to track a human subject performing the action specific to the particular scenario.
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Citations
20 Claims
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1. A method of retraining a general-purpose body-part tracker, the method comprising:
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receiving a set of different instances of scenario data, each instance of scenario data representing a human training-subject performing an action specific to a particular scenario; iterating over the set of different instances of scenario data with the general-purpose body-part tracker, the general-purpose body-part tracker previously trained using supervised machine learning to identify one or more general-purpose parameters to be used by the general-purpose body-part tracker to track a human subject; and identifying one or more special-purpose parameters to be selectively used to augment or replace the one or more general-purpose parameters if the general-purpose body-part tracker is used to track a human subject performing the action specific to the particular scenario; and associating the one or more special-purpose parameters with a scenario identifier that identifies the particular scenario for which the special-purpose parameters are to be selectively used by the general-purpose body-part tracker to track a human subject. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A storage device holding instructions, the instructions defining a body-part tracker, the instructions executable by a logic device to:
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receive a set of different instances of scenario data, each instance of scenario data representing a human training-subject performing an action specific to a particular scenario; iterate over the set of different instances of scenario data with the general-purpose body-part tracker, the general-purpose body-part tracker previously trained using supervised machine learning to identify one or more general-purpose parameters to be used by the general-purpose body-part tracker to track a human subject; and identify one or more special-purpose parameters to be selectively used to augment or replace the one or more general-purpose parameters if the general-purpose body-part tracker is used to track a human subject performing the action specific to the particular scenario, the one or more special-purpose parameters based on iteration over the set of different instances of scenario data; receive input data representing a human subject performing the action specific to the particular scenario;
receive an indication of applicability of the one or more special-purpose parameters to the input data;
analyze the input data with the general-purpose body-part tracker using the one or more special-purpose parameters indicated as being applicable to the input data to identify a body model of the human subject performing the action. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A method of tracking a human subject, the method comprising:
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receiving input data including a depth image representing a depth-camera recording of a human subject performing an action; receiving a scenario identifier indicated as being applicable to the input data; retrieving one or more special-purpose parameters associated with the scenario identifier from a data store; and analyzing the input data with a general-purpose body-part tracker using the one or more special-purpose parameters that augment or replace one or more general-purpose parameters to identify a body model representing the human subject performing the action; the general-purpose body-part tracker previously trained using unsupervised machine learning to identify the one or more special-purpose parameters after being initially trained using supervised machine learning to identify the one or more general-purpose parameters. - View Dependent Claims (19, 20)
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Specification