SYSTEM TO COMPILE LANDMARK IMAGE SEARCH RESULTS

• US 20120066219A1
• Filed: 11/22/2011
• Published: 03/15/2012
• Est. Priority Date: 05/23/2008
• Status: Active Grant

• Current Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Original Assignee: Lyndon Kennedy, Mor Naaman
• Inventors: Naaman, Mor, Kennedy, Lyndon
• Granted Patent: US 9,171,231 B2
• Time in Patent Office: Days
• US Class Current: 707/724
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06F 18/232 Non-hierarchical techniques
• CPC Class Codes: G06V 10/462 Salient features, e.g. scale invariant feature transforms [SIFT]
• CPC Class Codes: G06V 10/763 Non-hierarchical techniques, e.g. based on statistics of modelling distributions

Abstract

This patent discloses a system to compile a landmark image search result. The system may determine a rank of each image within a visual cluster according to at least one of a low-level self-similarity score, a low-level discriminative modeling score, and a point wise linking score. The landmark image search result may be compiled as a function of the rank of each image.

Claims

1. A method to compile an image search result, the method comprising:

receiving a plurality of images and tags for the images, a tag comprising a location corresponding to one of the images;

grouping the images into a plurality of clusters based on the location corresponding to the images, a cluster comprising a plurality of images;

grouping the images of the clusters into a plurality of visual clusters based on visual features of the images;

determining, using a computer, a rank of the images within the visual clusters; and

compiling the image search result at least partly based on the rank of the images within the visual clusters.

2. The method of claim 1, wherein the images comprise photographs, the location corresponding to the images comprises a location where the photograph was taken by a user.

3. The method of claim 1, wherein the grouping of the images into a plurality of clusters based on the location corresponding to the images comprises grouping the images into one of the clusters based on a geographical distance of the location corresponding to the images from a geographical location point associated with one of the clusters.

4. The method of claim 1, wherein the tags further comprise at least one keyword corresponding to the images, the grouping of the images into the plurality of clusters is based on the at least one keyword corresponding to the images.

5. The method of claim 4, wherein the grouping of the images into the clusters based on the at least one keyword further comprises determining if the keyword corresponding to the images is event driven or location driven.

6. The method of claim 5, wherein an event driven keyword is associated with a temporal pattern and a location driven keyword is associated with a spatial pattern.

7. The method of claim 1, wherein the rank of the images within the visual clusters is further based on a number of users associated with the visual clusters.

8. A system, comprising at least one processor and memory, to compile an image search result, the system comprising:

a module to receive a plurality of images and tags for the images, a tag comprising a location corresponding to one of the images;

a module to group the images into a plurality of clusters based on the location corresponding to the images, a cluster comprising a plurality of images;

a module to group the images of the clusters into a plurality of visual clusters based on visual features of the images;

a module to determine a rank of the images within the visual clusters; and

a module to compile the image search result at least partly based on the rank of the images within the visual clusters.

9. The system of claim 8, wherein the images comprise photographs, the location corresponding to the images comprises a location where the photograph was taken by a user.

10. The system of claim 8, wherein the grouping of the images into a plurality of clusters based on the location corresponding to the images comprises grouping the images into one of the clusters based on a geographical distance of the location corresponding to the images from a geographical location point associated with one of the clusters.

11. The system of claim 8, wherein the tags further comprise at least one keyword corresponding to the images, the grouping of the images into the plurality of clusters is based on the at least one keyword corresponding to the images.

12. The system of claim 11, wherein the grouping of the images into the clusters based on the at least one keyword further comprises determining if the keyword corresponding to the images is event driven or location driven.

13. The system of claim 12, wherein an event driven keyword is associated with a temporal pattern and a location driven keyword is associated with a spatial pattern.

14. The system of claim 8, wherein the rank of the images within the visual clusters is further based on a number of users associated with the visual clusters.

15. A non-transitory computer readable medium comprising a set of instructions which, when executed by a computer, cause the computer to compile an image search result, the instructions for:

receiving a plurality of images and tags for the images, a tag comprising a location corresponding to one of the images;

grouping the images into a plurality of clusters based on the location corresponding to the images, a cluster comprising a plurality of images;

grouping the images of the clusters into a plurality of visual clusters based on visual features of the images;

determining a rank of the images within the visual clusters; and

compiling the image search result at least partly based on the rank of the images within the visual clusters.

16. The non-transitory computer readable medium of claim 15, wherein the images comprise photographs, the location corresponding to the images comprises a location where the photograph was taken by a user.

17. The non-transitory computer readable medium of claim 15, wherein the grouping of the images into a plurality of clusters based on the location corresponding to the images comprises grouping the images into one of the clusters based on a geographical distance of the location corresponding to the images from a geographical location point associated with one of the clusters.

18. The non-transitory computer readable medium of claim 15, wherein the tags further comprise at least one keyword corresponding to the images, the grouping of the images into the plurality of clusters is based on the at least one keyword corresponding to the images.

19. The non-transitory computer readable medium of claim 18, wherein the grouping of the images into the clusters based on the at least one keyword further comprises determining if the keyword corresponding to the images is event driven or location driven.

20. The non-transitory computer readable medium of claim 19, wherein an event driven keyword is associated with a temporal pattern and a location driven keyword is associated with a spatial pattern.