Co-location visual pattern mining for near-duplicate image retrieval
First Claim
1. In a computing environment, a computer-implemented method comprising:
- performing near-duplicate image retrieval with a computer processor, including detecting, with the computer processor, visual patterns in images, representing the visual patterns as visual pattern vectors, and using the visual pattern vectors and visual word vectors to determine, with the computer processor, similarity between images by ranking database images according to a similarity of each given database image with a query image, including by obtaining a query visual pattern vector for the query image, and for each given image, determining a visual pattern vector and computing a visual pattern-based similarity score for the given image by selecting a set of most similar database images based on a ranking of the database images according to the visual pattern-based similarity scores, and re-ranking the set of most similar database images by evaluating similarity for each specific image in the set of most similar database images via a visual word vector corresponding to the specific image and a query visual word vector corresponding to the query image.
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Accused Products
Abstract
Described is a technology in which image near-duplicate retrieval is performed using similarities between patterns of query image words and patterns of database image words. In general, the image retrieval problems resulting from visual polysemy are reduced by using such visual patterns. Visual word vectors and visual pattern vectors are determined for the query image and a database image. These four vectors are used to determine similarity between the database image and the query image. The similarity scores may be used for ranking and/or re-ranking the database image similarity to the query image relative to other database images'"'"' similarity scores. Also described is expanding a query visual word of the query image to a set of visual words that are visual synonyms with the query visual word, to help reduce image retrieval problems resulting from visual synonymy.
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Citations
17 Claims
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1. In a computing environment, a computer-implemented method comprising:
performing near-duplicate image retrieval with a computer processor, including detecting, with the computer processor, visual patterns in images, representing the visual patterns as visual pattern vectors, and using the visual pattern vectors and visual word vectors to determine, with the computer processor, similarity between images by ranking database images according to a similarity of each given database image with a query image, including by obtaining a query visual pattern vector for the query image, and for each given image, determining a visual pattern vector and computing a visual pattern-based similarity score for the given image by selecting a set of most similar database images based on a ranking of the database images according to the visual pattern-based similarity scores, and re-ranking the set of most similar database images by evaluating similarity for each specific image in the set of most similar database images via a visual word vector corresponding to the specific image and a query visual word vector corresponding to the query image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. In a computing environment, a system comprising:
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a query image processing subsystem that determines a query image word vector for the query image and a query pattern word vector for the query image, and a database image ranking subsystem that ranks database images with respect to similarity of each database image to the query image, including obtaining an image word vector and a pattern word vector for each database image, and, for each database image, using the query image word vector for the query image, the query pattern word vector for the query image, the image word vector for the database image, and the pattern word vector for the database image to determine a score for the similarity of each database image to the query image wherein the database image ranking subsystem uses the query image word vector for the query image, the query pattern word vector for the query image, the image word vector for the database image, and the pattern word vector for the database image to determine a score of the similarity of the database image to the query image by ranking database images according to a similarity score, for each image with the query image via visual word vector-based scoring, selecting a set of most similar images based on the ranking according to the visual word vector-based scoring, and re-ranking the set according to the similarity of each image pattern vector-based similarity score with respect to the query pattern word vector; and the system further comprising a computer processor being a functional component of the system and activated by the query image processing system and database image ranking system to facilitate determining the query image word vector and query pattern word vector and ranking the database images. - View Dependent Claims (10, 11, 12, 13, 14)
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15. One or more computer storage media having computer-executable instructions, the computer storage media being a hardware storage media, the instructions, when executed, perform steps, comprising:
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receiving a query image; determining a visual word vector for the query image; determining a visual pattern vector for the query image; determining similarity with each image of a set of database images, including, for each image of the set of database images, computing a first similarity score by evaluating the visual word vector for the query image with a visual word vector for each database image and computing a second similarity score by evaluating the visual pattern vector for the query image with a visual pattern vector for each database image; and using the first and second similarity scores according to a usage model by ranking the set of database images based on one of the first and second similarity scores, and re-ranking a selected set of highest ranked database images in the set of database images based on another of the first and second similarity score. - View Dependent Claims (16, 17)
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Specification