IMAGE CONCEALING VIA EFFICIENT FEATURE SELECTION
First Claim
Patent Images
1. A method comprising:
- automatically dividing an initial feature representation of an image into two or more subsets;
selecting at least one representative feature from each of the one or more subsets;
estimating a warping parameter for the image using the at least one representative feature from each of the one or more subsets.
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Abstract
A novel technique for unsupervised feature selection is disclosed. The disclosed methods include automatically selecting a subset of a feature of an image. Additionally, the selection of the subset of features may be incorporated with a congealing algorithm, such as a least-square-based congealing algorithm. By selecting a subset of the feature representation of an image, redundant and/or irrelevant features may be reduced or removed, and the efficiency and accuracy of least-square-based congealing may be improved.
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Citations
20 Claims
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1. A method comprising:
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automatically dividing an initial feature representation of an image into two or more subsets; selecting at least one representative feature from each of the one or more subsets; estimating a warping parameter for the image using the at least one representative feature from each of the one or more subsets. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method, comprising:
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automatically identifying a first subset of features of a first image, wherein the first image is selected from a plurality of images; and automatically identifying a second subset of features of a second image, wherein the second image is selected from a plurality of images; and estimating warping parameters for the first image and the second image using the first subset of features and the second subset of features. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. A method, comprising:
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executing an unsupervised feature selection algorithm, comprising; constructing a graph having features of an image as vertices; determining a connectivity between the vertices using a maximum information compression index; partitioning the graph into two or more subsets of features using a power iteration clustering algorithm; and selecting representative features from each subset of features; and executing an image congealing algorithm using the subsets of features. - View Dependent Claims (17, 18, 19, 20)
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Specification