AUTOMATIC EVENT RECOGNITION AND CROSS-USER PHOTO CLUSTERING

• US 20120213404A1
• Filed: 08/29/2011
• Published: 08/23/2012
• Est. Priority Date: 02/18/2011
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Steiner, Matthew S.
• Application Number:
  US13/219,835
• Publication Number:
  US 20120213404A1
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06F 16/5866 using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06V 20/30 in albums, collections or shared content, e.g. social network photos or video

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatic event recognition and photo clustering. In one aspect, methods include receiving, from a first user, first image data corresponding to a first image, receiving, from a second user, second image data corresponding to a second image, comparing the first image data and the second image data, and determining that the first image and the second image correspond to a coincident event based on the comparing.

Claims

1. A system comprising:

a data processing apparatus; and

a computer storage medium encoded with a computer program, the program comprising instructions that when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising;

receiving, from a first user, first image data corresponding to a first image;

receiving, from a second user, second image data corresponding to a second image;

comparing the first image data and the second image data; and

determining that the first image and the second image each correspond to an event based on the comparing, the event being coincident with respect to the first image and the second image.

2. The system of claim 1, the operations further comprising providing an indication to the first user, the indication indicating that the second user has an image corresponding to the coincident event.

3. The system of claim 2, the operations further comprising receiving input from the first user, the input indicating a request to add the second image to a collection of images associated with the coincident event.

4. The system of claim 3, the operations further comprising providing the request to the second user.

5. The system of claim 4, the operations further comprising receiving input from the second user, the input indicating a response to the request.

6. The system of claim 1, wherein the second user is a member of a social network of the first user.

7. The system of claim 1, wherein the second user is a person determined to be in the first image.

8. The system of claim 1, wherein the second user is a member of a social network of a person determined to be in the first image.

9. The system of claim 1, wherein the first image data comprises a first timestamp and the second image data comprises a second timestamp.

10. The system of claim 9, wherein comparing the first image data and the second image data comprises:

determining a difference between the first timestamp and the second timestamp; and

determining that the difference is less than a threshold difference.

11. The system of claim 1, wherein the first image data comprises first geo-location data and the second image data comprises second geo-location data.

12. The system of claim 11, wherein comparing the first image data and the second image data comprises:

determining a distance between the first geo-location and the second geo-location; and

determining that the distance is less than a threshold distance.

13. The system of claim 1, wherein the first image data comprises first check-in data and the second image data comprises second check-in data.

14. The system of claim 13, wherein comparing the first image data and the second image data comprises:

determining a first location specified by the first check-in data;

determining a second location specified by the second check-in data; and

determining that the first and second locations refer to a same geographical location.

15. The system of claim 1, wherein the first image data and the second image data each comprise at least one of timestamp data, geo-location data, check-in data, and content data.

16. The system of claim 15, wherein comparing the first image data and the second image data comprises:

processing the content data of the first image data and the second image data; and

identifying a landmark as being present in both the first image and the second image.

17. The system of claim 15, wherein comparing the first image data and the second image data comprises:

processing the content data of the first image data and the second image data; and

identifying a human face as being present in both the first image and the second image.

18. The system of claim 1, wherein the first image data and the second image data each comprise ancillary data, the ancillary data comprising data added to the first image data and the second image data after generation of the first image data and the second image data.

19. The system of claim 18, wherein the ancillary data comprises one or more tags indicating a presence of one or more particular persons in each of the first image and the second image.

20. The system of claim 1, the operations further comprising:

generating a confidence score based on the comparing; and

determining that the confidence score exceeds a threshold confidence score, wherein determining that the first image and the second image correspond to a coincident event is based on the confidence score exceeding the threshold confidence score.

21. A computer-readable medium coupled to one or more processors having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving, from a first user, first image data corresponding to a first image;

receiving, from a second user, second image data corresponding to a second image;

comparing the first image data and the second image data; and

determining that the first image and the second image each correspond to an event based on the comparing, the event being coincident with respect to the first image and the second image.

22. A computer-implemented method, comprising:

receiving, from a first user, first image data corresponding to a first image;

receiving, from a second user, second image data corresponding to a second image;

comparing the first image data and the second image data; and

determining that the first image and the second image each correspond to an event based on the comparing, the event being coincident with respect to the first image and the second image.