Method and apparatus for arbitrating outputs from multiple pattern recognition classifiers
First Claim
1. A computer readable medium, storing computer executable instructions thereon for classifying an input image into one of a plurality of output classes comprising at least three classes, said executable instructions, when executed by a processor, performing the following process:
- determining a candidate output class, at least one rejected output class, and an associated confidence value from a set of associated output classes at each of a plurality of classifiers;
selecting a classifier from the plurality of classifiers having a best confidence value;
eliminating the at least one rejected class at the selected classifier from consideration as the associated class for the input image; and
iteratively repeating the following steps until only one output class remains;
defining a subset of classifiers associated with the candidate output class from the selected classifier;
selecting a new classifier having the best associated confidence value within the defined subset; and
eliminating the at least one rejected classes determined at the selected new classifier from consideration as the associated class for the input image.
2 Assignments
0 Petitions
Accused Products
Abstract
A system (400) for classifying an input image into one of a plurality of output classes includes a plurality of pattern recognition classifiers (420, 422, 424). Each of the plurality of pattern recognition classifiers determines a candidate output class and at least one rejected output class for the input image from an associated subset of the plurality of output classes. Each classifier generates a confidence value associated with the classifier based on the determination. An arbitrator (430) selects a classifier having the best associated confidence value and eliminates the at least one rejected class determined at the selected classifier from consideration as the associated class for the input image.
51 Citations
16 Claims
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1. A computer readable medium, storing computer executable instructions thereon for classifying an input image into one of a plurality of output classes comprising at least three classes, said executable instructions, when executed by a processor, performing the following process:
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determining a candidate output class, at least one rejected output class, and an associated confidence value from a set of associated output classes at each of a plurality of classifiers; selecting a classifier from the plurality of classifiers having a best confidence value; eliminating the at least one rejected class at the selected classifier from consideration as the associated class for the input image; and iteratively repeating the following steps until only one output class remains; defining a subset of classifiers associated with the candidate output class from the selected classifier; selecting a new classifier having the best associated confidence value within the defined subset; and eliminating the at least one rejected classes determined at the selected new classifier from consideration as the associated class for the input image.
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2. A system for classifying image data associated with a vehicle occupant safety system into an associated one of a plurality of output classes, said system comprising:
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a camera that images a vehicle interior to provide an input image; a plurality of pattern recognition classifiers, each of the plurality of pattern recognition classifiers having associated first and second output classes from the plurality of output classes and being operative to select one of the first and second output classes as a candidate output class for the input image and the other of the first and second output classes as a rejected output class and generate a confidence value associated with the classifier based on the selection; an arbitrator that conducts an iterative process until only one of the plurality of pattern recognition classifiers, and its associated selected output class, remain, wherein at each iteration, the arbitrator selects a classifier having a best associated confidence value from a classifier set initially comprising the plurality of classifiers, determines the rejected class associated with the selected classifier, and removes each classifier within the classifier set having the rejected class as one of its associated first and second output classes, such that in the next iteration, the classifier set will include only classifiers that do not have the rejected class as one of its associated first and second output classes. - View Dependent Claims (3, 4, 5, 6, 7, 8, 9)
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10. A method for classifying an input image into an associated one of a plurality of output classes comprising the steps of:
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determining a candidate output class, at least one rejected output class, and an associated confidence value from a set of associated output classes at each of a plurality of classifiers; selecting a classifier from the plurality of classifiers having a best confidence value; eliminating the at least one rejected class at the selected classifier from consideration as the associated class for the input image; and iteratively repeating the following steps until only one output class remains; defining a subset of classifiers associated with the candidate output class from the selected classifier; selecting a new classifier having the best associated confidence value within the defined subset; and eliminating the at least one rejected classes determined at the selected new classifier from consideration as the associated class for the input image. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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Specification