Method and system for optimizing accuracy-specificity trade-offs in large scale visual recognition
First Claim
Patent Images
1. A computerized method for classifying images, comprising:
- receiving an image hierarchy;
receiving a first image of interest wherein the image includes at least one feature;
classifying the at least one feature of the image according to the image hierarchy;
generating a dual variable for a Lagrange function associated with the classification of the at least one feature, where the dual variable controls a trade-off between an information gain and an accuracy;
optimizing the classification of the at least one feature of the image using the dual variable controlling the trade-off between the information gain and the accuracy by generating a classifier that maximizes a relationship between the information gain and the accuracy with respect to the dual variable; and
generating at least one optimized classification of the at least one feature of the image for the first image of interest.
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Abstract
As visual recognition scales up to ever larger numbers of categories, maintaining high accuracy is increasingly difficult. Embodiment of the present invention include methods for optimizing accuracy-specificity trade-offs in large scale recognition where object categories form a semantic hierarchy consisting of many levels of abstraction.
3 Citations
20 Claims
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1. A computerized method for classifying images, comprising:
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receiving an image hierarchy; receiving a first image of interest wherein the image includes at least one feature; classifying the at least one feature of the image according to the image hierarchy; generating a dual variable for a Lagrange function associated with the classification of the at least one feature, where the dual variable controls a trade-off between an information gain and an accuracy; optimizing the classification of the at least one feature of the image using the dual variable controlling the trade-off between the information gain and the accuracy by generating a classifier that maximizes a relationship between the information gain and the accuracy with respect to the dual variable; and generating at least one optimized classification of the at least one feature of the image for the first image of interest. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An image classification system, comprising:
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a processor; a memory; where the processor is configured by software stored in memory to; receive an image hierarchy; receive a first image of interest wherein the image includes at least one feature; classify the at least one feature of the image according to the image hierarchy; generate a dual variable for a Lagrange function associated with the classification of the at least one feature, where the dual variable controls a trade-off between an information gain and an accuracy; optimize the classification of the at least one feature of the image using the dual variable controlling the trade-off between the information gain and the accuracy by generating a classifier that maximizes a relationship between the information gain and the accuracy with respect to the dual variable; and generate at least one optimized classification of the at least one feature of the image for the first image of interest. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification