METHOD FOR RANKING AND SELECTING EVENTS IN MEDIA COLLECTIONS
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.
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.