System or method for classifying target information captured by a sensor
First Claim
1. A classification system for generating a classification of target information obtained with a sensor, said classification system comprising:
- a grouping subsystem, said grouping subsystem providing for a plurality of classes and a plurality of groups, wherein each said group includes at least one said class, and wherein at least one said group includes more than one said class; and
a selection subsystem, wherein said selection subsystem provides for generating said classification using said target information, wherein said classification is one said group from said plurality of groups.
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Abstract
The disclosure describes a system and method for classifying information relating to target attributes that are captured by a sensor (collectively “classification system”). A wide variety of sensors, classification categories (including potentially classes and groups of classes), targets, and purposes can influence the processing performed by the classification system. The classification system is not forced to arbitrarily identify a single class as the appropriate classification if two or more classes cannot be adequately distinguished from one another given the particular target attributes and processing results. The classification system can generate a classification relating to a group of classes, with the group including one, two, or even more than two classes, if such a conclusion is appropriate. Historical attributes, environmental factors, relevant events and the plausibility of transitions from one class to another, can be incorporated into the classification process.
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Citations
33 Claims
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1. A classification system for generating a classification of target information obtained with a sensor, said classification system comprising:
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a grouping subsystem, said grouping subsystem providing for a plurality of classes and a plurality of groups, wherein each said group includes at least one said class, and wherein at least one said group includes more than one said class; and
a selection subsystem, wherein said selection subsystem provides for generating said classification using said target information, wherein said classification is one said group from said plurality of groups. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A classification system for generating a classification from a plurality of target attributes obtained with a sensor, said classification system comprising:
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a processor, said processor providing for;
a classification;
a plurality of historical attributes;
a plurality of groups;
a plurality of classes;
a plurality of belief metrics; and
a plurality of plausibility metrics;
wherein each said group includes at least one said class;
wherein at least one said group includes more than one said class;
wherein said classification is one group within said plurality of groups; and
wherein said processor identifies said using at least one said historical attribute, at least one said belief metric, and at least one said plausibility metric. - View Dependent Claims (23, 24, 25, 26)
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27. A method for classifying a target using information obtained from a sensor, said method comprising:
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identifying one group from a plurality of predefined groups as an initial classification by analyzing the target information;
creating a belief metric relating to the initial classification generating a plausibility metric relating to the initial classification and the belief metric; and
transforming the initial classification into an enhanced classification, wherein the belief metric and the plausibility metric influence the transformation of the initial classification into the enhanced classification. - View Dependent Claims (28, 29, 30, 31)
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32. A method of implementing an occupant classifier for use in a vehicle safety restraint application, comprising:
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defining a disablement situation, a plurality of groups, and a plurality classes, wherein each group is defined to include at least one class, wherein at least one group is defined to include more than one class, and wherein at least one group is defined as the disablement situation;
implementing a selection heuristic to selectively identify one group within the plurality of groups as the classification, wherein the selection heuristic is configured to be influenced by a plausibility metric and a historical attribute; and
configuring the vehicle safety restraint application to preclude deployment when the identified group is defined as the disablement situation. - View Dependent Claims (33)
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Specification