Image ordering system optimized via user feedback
First Claim
1. A computer implemented method for ordering images, comprising an act of causing a computer having a processor to perform operations ofi. receiving, in the processor, a plurality of images;
- ii. extracting, from each image, image features;
iii. generating a set of all possible image pairs for all images;
iv. generating at least one similarity metric between the images in each image pair in the set;
1. if more than one similarity metric exists between the images in each image pair in the set, then generating a net similarity metric by combining the similarity metrics;
2. if only one similarity metric exists between the images in each image pair in the set, then a net similarity metric is the similarity metric; and
v. ordering the plurality of images according to the net similarity metrics to generate a computer-ordered set of images.
1 Assignment
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Accused Products
Abstract
Described is a system for ordering images. The system receives a plurality of images. Image features are extracted from each image. A set of all possible image pairs are generated for all images. A similarity metric with weights is generated between the images in each image pair in the set, with a net similarity metric thereafter generated by combining the similarity metrics. The images are then ordered according to the net similarity metrics to generate a computer-ordered set of images. The computer-ordered set of images is then displayed to the user, which allows the user to re-order the images to generate a user-ordered set of images. The weights are then optimized to minimize the distance between the computer-ordered set of images and the user-ordered set of images. The similarity metrics are then re-weighted, with the images thereafter being re-ordered according to the new metrics.
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Citations
23 Claims
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1. A computer implemented method for ordering images, comprising an act of causing a computer having a processor to perform operations of
i. receiving, in the processor, a plurality of images; -
ii. extracting, from each image, image features; iii. generating a set of all possible image pairs for all images; iv. generating at least one similarity metric between the images in each image pair in the set; 1. if more than one similarity metric exists between the images in each image pair in the set, then generating a net similarity metric by combining the similarity metrics; 2. if only one similarity metric exists between the images in each image pair in the set, then a net similarity metric is the similarity metric; and v. ordering the plurality of images according to the net similarity metrics to generate a computer-ordered set of images. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system for ordering images, comprising a processor configured to perform operations of:
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i. receiving, in the processor, a plurality of images; ii. extracting, from each image, image features; iii. generating a set of all possible image pairs for all images; iv. generating at least one similarity metric between the images in each image pair in the set; 1. if more than one similarity metric exists between the images in each image pair in the set, then generating a net similarity metric by combining the similarity metrics; 2. if only one similarity metric exists between the images in each image pair in the set, then a net similarity metric is the similarity metric; and v. ordering the plurality of images according to the net similarity metrics to generate a computer-ordered set of images. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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17. A computer program product for ordering images, the computer program product comprising computer-readable instruction means stored on a non-transitory computer-readable medium that are executable by a computer having a processor for causing the processor to perform operations of:
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i. receiving, in the processor, a plurality of images; ii. extracting, from each image, image features; iii. generating a set of all possible image pairs for all images; iv. generating at least one similarity metric between the images in each image pair in the set; 1. if more than one similarity metric exists between the images in each image pair in the set, then generating a net similarity metric by combining the similarity metrics; 2. if only one similarity metric exists between the images in each image pair in the set, then a net similarity metric is the similarity metric; and v. ordering the plurality of images according to the net similarity metrics to generate a computer-ordered set of images. - View Dependent Claims (18, 19, 20, 21, 22, 23)
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Specification