Reranking using confident image samples

US9384241B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9384241-B2
Application numberUS-201113393509-A
CountryUS
Kind codeB2
Filing dateNov 24, 2011
Priority dateNov 24, 2011
Publication dateJul 5, 2016
Grant dateJul 5, 2016

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

The techniques described herein determine an initial set of ranked images associated with an image-based search query. Based on visual content similarities between images in the initial set of ranked images, the techniques select confident image samples from the initial set of ranked images. The techniques then use the confident image samples to rerank the initial set of ranked images. Accordingly, a search engine uses the confident image samples to promote images that are likely to be relevant to the search query, while demoting images that are not likely to be relevant to the search query. Therefore, the search engine can provide improved relevance-based search results to an image-based search query.

First claim

Opening claim text (preview).

The invention claimed is: 1. A method comprising: receiving a search query; ranking, based at least in part on the search query, a set of images to provide a set of ranked images; extracting visual features for individual images of the set of ranked images; determining, by one or more processors and based at least in part on the extracted visual features, a first degree of visual content similarity for individual images of the set of ranked images with respect to one or more other images of the set of ranked images; implementing, by the one or more processors, a selection algorithm to automatically select at least two confident image samples from the set of ranked images based at least in part on the first degrees of visual content similarity and based at least in part on ranking positions of individual images within the set of ranked images, wherein the at least two confident image samples automatically selected are not consecutively ordered within the set of ranked images; determining, by the one or more processors and based at least in part on the extracted visual features, a second degree of visual content similarity for individual images of the set of ranked images with respect to the at least two confident image samples; and reranking the set of ranked images based at least in part on the second degrees of visual content similarity. 2. The method as recited in claim 1 , further comprising providing at least a portion of the set of reranked images as search results in response to receiving the search query. 3. The method as recited in claim 1 , wherein reranking the set of ranked images comprises promoting images that are visually similar to the at least two confident image samples and demoting images that are not visually similar to the at least two confident image samples. 4. The method as recited in claim 1 , wherein the first degree of visual content similarity for a given image is determined based on comparing the extracted visual features associated with the given image to the extracted visual features associated with the one or more other images of the set of ranked images. 5. The method as recited in claim 1 , further comprising implementing a non-negative least squares relaxation algorithm to automatically select the at least two confident image samples from the set of ranked images. 6. The method as recited in claim 1 , further comprising implementing a bounded-variable least squares relaxation algorithm to automatically select the at least two confident image samples from the set of ranked images. 7. The method as recited in claim 1 , further comprising implementing an adapted kernel-based reranking process to rerank the set of ranked images based at least in part on the second degrees of visual content similarity. 8. The method as recited in claim 1 , wherein the set of ranked images associated with the search query is determined based at least in part on matching query terms with textual information corresponding to individual images of the set of ranked images. 9. A system comprising: one or more processors; a memory, coupled to the one or more processors, storing: an image ranking module, operable by the one or more processors, that ranks images associated with a search query based at least in part on textual matching, thereby providing a set of ranked images; an image feature extraction module, operable by the one or more processors, that extracts visual features from individual ones of the set of ranked images; a confident sample selection module, operable by the one or more processors, that determines, based at least in part on the extracted visual features, a first degree of visual content similarity for individual ones of the set of ranked images with respect to one or more other images of the set of ranked images and that implements a selection algorithm to automatically select at least two non-consecutively ordered confident image samples based at least in part on the first degrees of visual content similarity and based at least in part on ranking positions of individual images within the set of ranked images; and a reranking module, operable by the one or more processors, that determines, based at least in part on the extracted visual features, a second degree of visual content similarity for individual ones of the set of ranked images with respect to the at least two non-consecutively ordered confident image samples and that reranks the set of ranked images based at least in part on the second degrees of visual content similarity. 10. The system as recited in claim 9 , wherein the first degree of visual content similarity for a given image is determined based on comparing the extracted visual features associated with the given image to the extracted visual features associated with the one or more other images of the set of ranked images. 11. The system as recited in claim 9 , wherein the confident sample selection module implements a non-negative least squares relaxation algorithm to automatically select the at least two non-consecutively ordered confident image samples from the set of ranked images. 12. The system as recited in claim 9 , wherein the confident sample selection module implements a bounded-variable least squares relaxation algorithm to automatically select the at least two non-consecutively ordered confident image samples from the set of ranked images. 13. The system as recited in claim 9 , wherein the reranking module implements an adapted kernel-based reranking process to rerank the set of ranked images based at least in part on the second degrees of visual content similarity. 14. The system as recited in claim 9 , wherein the at least two non-consecutively ordered confident image samples automatically selected are not consecutively ordered highest ranked images within the set of ranked images. 15. One or more computer storage media comprising instructions that, when executed, configure a computer device to perform operations comprising: receiving a search query; ranking a set of images based at least in part on terms used in the search query; extracting visual features for individual images of the set of ranked images; determining, based at least in part on the extracted visual features, a first degree of visual content similarity for individual images of the set of ranked images with respect to one or more other images of the set of ranked images; implementing a selection algorithm to automatically select at least two non-consecutively ordered confident image samples from the set of ranked images based at least in part on the first degrees of visual content similarity and based at least in part on ranking positions of individual images within the set of ranked images; determining, based at least in part on the extracted visual features, a second degree of visual content similarity for individual images of the set of ranked images with respect to the at least two non-consecutively ordered confident image samples; reranking the set of ranked images based at least in part on the second degrees of visual content similarity; and providing at least a portion of the reranked set of images as search results. 16. The one or more computer storage media recited in claim 15 , wherein reranking the set of ranked images comprises promoting images that are visually similar to the at least two non-consecutively ordered confident image samples and demoting images that are not visually similar to the at least two non-consecutively ordered confident image samples. 17. The one or more computer storage media recited in claim 15 , furth

Assignees

Inventors

Classifications

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US9384241B2 cover?
The techniques described herein determine an initial set of ranked images associated with an image-based search query. Based on visual content similarities between images in the initial set of ranked images, the techniques select confident image samples from the initial set of ranked images. The techniques then use the confident image samples to rerank the initial set of ranked images. Accordin…
Who is the assignee on this patent?
Wang Jingdong, Li Shipeng, Morioka Nobuyuki, and 1 more
What technology area does this patent fall under?
Primary CPC classification G06F17/3053. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jul 05 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).