Identifying textual terms in response to a visual query
First Claim
Patent Images
1. A computer-implemented method comprising:
- receiving a query image;
obtaining a set of image features that are associated with the query image;
obtaining a vector of image feature values for the set of image features;
obtaining a set of query terms that correspond to the set of image features;
for each query term of the set, obtaining a weight for the query term by applying the vector of image feature values to a respective image relevance vector for the query term, wherein each component of the image relevance vector indicates a relative importance of each corresponding component in the vector of image feature values in determining whether the query term is relevant;
selecting a subset of the query terms based on the respective weight for each query term;
andproviding, for output, one or more of the query terms of the subset of the query terms.
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Abstract
A method, system, and computer readable storage medium is provided for identifying textual terms in response to a visual query is provided. A server system receives a visual query from a client system. The visual query is responded to as follows. A set of image feature values for the visual query is generated. The set of image feature values is mapped to a plurality of textual terms, including a weight for each of the textual terms in the plurality of textual terms. The textual terms are ranked in accordance with the weights of the textual terms. Then, in accordance with the ranking the textual terms, one or more of the ranked textual terms are sent to the client system.
68 Citations
17 Claims
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1. A computer-implemented method comprising:
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receiving a query image; obtaining a set of image features that are associated with the query image; obtaining a vector of image feature values for the set of image features; obtaining a set of query terms that correspond to the set of image features; for each query term of the set, obtaining a weight for the query term by applying the vector of image feature values to a respective image relevance vector for the query term, wherein each component of the image relevance vector indicates a relative importance of each corresponding component in the vector of image feature values in determining whether the query term is relevant; selecting a subset of the query terms based on the respective weight for each query term; and providing, for output, one or more of the query terms of the subset of the query terms. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system comprising:
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one or more computers and one or more storage devices storing instructions that are configured to, when executed by the one or more computers, to cause the one or more computers to perform operations comprising; receiving a query image; obtaining a set of image features that are associated with the query image; obtaining a vector of image feature values for the set of image features; obtaining a set of query terms that correspond to the set of image features; for each query term of the set, obtaining a weight for the query term by applying the vector of image feature values to a respective image relevance vector for the query term, wherein each component of the image relevance vector indicates a relative importance of each corresponding component in the vector of image feature values in determining whether the query term is relevant; selecting a subset of the query terms based on the respective weight for each query term; and providing, for output, one or more of the query terms of the subset of the query terms. - View Dependent Claims (9, 10, 11, 12, 13)
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14. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:
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receiving a query image; obtaining a set of image features that are associated with the query image; obtaining a vector of image feature values for the set of image features; obtaining a set of query terms that correspond to the set of image features, for each query term of the set, obtaining a weight for the query term by applying the vector of image feature values to a respective image relevance vector for the query term, wherein each component of the image relevance vector indicates a relative importance of each corresponding component in the vector of image feature values in determining whether the query term is relevant; selecting a subset of the query terms based on the respective weight for each query term; and providing, for output, one or more of the query terms of the subset of the query terms. - View Dependent Claims (15, 16, 17)
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Specification