METHOD FOR RANKING AND SELECTING EVENTS IN MEDIA COLLECTIONS

• US 20150006523A1
• Filed: 06/20/2014
• Published: 01/01/2015
• Est. Priority Date: 06/27/2013
• Status: Active Grant

• Current Assignee: Kodak Alaris Inc (KPP (no. 2) Trustees Ltd.)
• Original Assignee: Kodak Alaris Inc (KPP (no. 2) Trustees Ltd.)
• Inventors: Das, Madirakshi, Loui, Alexander C.
• Granted Patent: US 11,080,318 B2
• Time in Patent Office: Days
• US Class Current: 707/725
• CPC Class Codes: G06F 16/41 Indexing; Data structures therefor; Storage structures

Abstract

A method for ranking events in media collections includes designating a media collection, using a processor to cluster the media collection items into a hierarchical event structure, using the processor to identify and count visually similar sub-events within each event in the hierarchical event structure, using the processor to determine a ranking of events based on the count of sub-events within each event, and associating the determined ranking with each event in the media collection.

Claims

1. A method for ranking events in media collections, comprising;

designating a media collection;

using a processor to cluster the media collection items into a hierarchical event structure;

using the processor to identify and count visually similar sub-events within each event in the hierarchical event structure;

using the processor to determine a ranking of events based on the count of sub-events within each event; and

associating the determined ranking with each event in the media collection.

2. The method of claim 1, wherein the ranking of events is based on the significance score of the event.

3. The method of claim 1, wherein the ranking of events is based on a distribution that models the importance of an event over an elapsed time period.

4. The method of claim 1, wherein the ranking of events is based on a score or distribution that models the interestingness of an event over an elapsed time period.

5. The method of claim 1, wherein the ranking of events is based on metadata from social networks such as number of likes and comments.

6. The method of claim 1, wherein the ranking of events is based on metadata from social networks through the analysis of user tags and comments.

7. The method of claim 1, wherein the ranking of events is based on the number of images in the event that have been marked by the user as being a favorite or to be used for sharing.

8. A method for selecting events from media collections, comprising;

designating a media collection;

using a processor to cluster the media collection items into a hierarchical event structure;

using the processor to identify and count visually similar sub-events within each event in the hierarchical event structure;

using the processor to determine a ranked list of events based on the count of sub-events within each event;

using the processor to calculate a target distribution that is based on the distribution of one or more event attributes of the events derived from the media collection; and

selecting events from the ranked list of events based on the calculated target distribution.

9. The method of claim 8, wherein the event attribute used in the target distribution is the event class.

10. The method of claim 8, wherein the event attribute used in the target distribution is the event size.

11. The method of claim 8, wherein the event attribute used in the target distribution is the media type of the event.

12. The method of claim 8, wherein the ranking of events is based on the significance score of the event.

13. The method of claim 8, wherein the ranking of events is based on a distribution that models the importance of an event over an elapsed time period.

14. The method of claim 8, wherein the ranking of events is based on scores or a distribution that models the interestingness of an event over an elapsed time period.

15. The method of claim 8, wherein the ranking of events is based on metadata from social networks such as number of likes and comments.

16. The method of claim 8, wherein the ranking of events is based on metadata from social networks through the analysis of user tags and comments.

17. The method of claim 8, wherein the ranking of events is based on the number of images in the event that have been marked by the user as being a favorite or to be used for sharing.