Adaptive event timeline in consumer image collections

Abstract

A method for organizing an event timeline for a digital image collection, includes using a processor for detecting events in the digital image collection and each event's associated timespan; determining the detected events that are significant in the digital image collection; and organizing the event timeline so that the event timeline shows the significant events and a clustered representation of the other events, made available to the user at different time granularities. The organized event timeline is also used for selecting images for generating output.

What is claimed is: 
     
         1 . A method comprising:
 detecting, by a computing device, a plurality of events in a plurality of digital images and an associated timespan for each event of the plurality of events;   generating a time series that indicates a number of images captured during a time period covered by the digital image collection;   identifying a set of events by analyzing the time series using time-series modeling; and   organizing, by the computing device, the plurality of events into an event timeline, such that detected events on an event timeline between the determined set of events are grouped into clusters on the event timeline.   
     
     
         2 . The method of  claim 1 , wherein the detecting the plurality of events comprises detecting the plurality of events based on a selected time granularity. 
     
     
         3 . The method of  claim 2 , wherein selecting the granularity of event detection is based on choosing the fewest detected events that preserve the significant events during a given time period. 
     
     
         4 . The method of  claim 1 , further comprising enabling user browsing of images associated with at least one detected event of the plurality of events. 
     
     
         5 . The method of  claim 1 , further comprising:
 presenting a display of the event timeline; and   receiving a user selection of the event timeline.   
     
     
         6 . The method of  claim 4 , further comprising enabling user browsing of images associated with at least one detected event of the plurality of events for the selected first event timeline. 
     
     
         7 . The method of  claim 1 , further comprising:
 producing an emphasis score using an emphasis operator; and   controlling a presentation of an output of images based on the emphasis score.   
     
     
         8 . The method of  claim 1 , further comprising analyzing the time series to find a model that identifies the significant events. 
     
     
         9 . The method of  claim 8 , wherein the identifying comprises determining when the model is less able to predict actual data of the time series. 
     
     
         10 . A system comprising:
 a memory; and   a processor coupled to the memory, wherein the processor is configured to:
 detect a plurality of events in a plurality of digital images and an associated timespan for each event of the plurality of events; 
 generate a time series that indicates a number of images captured during a time period covered by the digital image collection; 
 identify a set of events by analyzing the time series using time-series modeling; and 
 organize the plurality of events into an event timeline, such that detected events on an event timeline between the determined set of events are grouped into clusters on the event timeline. 
   
     
     
         11 . The system of  claim 10 , wherein the detection of the plurality of events comprises a detection of the plurality of events based on a selected time granularity. 
     
     
         12 . The system of  claim 11 , wherein the selection of the granularity of event detection is based on choosing the fewest detected events that preserve the significant events during a given time period. 
     
     
         13 . The system of  claim 10 , wherein the processor is further configured to enable user browsing of images associated with at least one detected event of the plurality of events. 
     
     
         14 . The system of  claim 10 , wherein the processor is further configured to:
 present a display of the event timeline; and   receive a user selection of the event timeline.   
     
     
         15 . The system of  claim 10 , wherein the processor is further configured to:
 produce an emphasis score using an emphasis operator; and   control a presentation of an output of images based on the emphasis score.   
     
     
         16 . A non-transitory computer-readable medium having instructions stored thereon that, upon execution by a computing device, cause the computing device to perform operations comprising:
 detecting a plurality of events in a plurality of digital images and an associated timespan for each event of the plurality of events;   generating a time series that indicates a number of images captured during a time period covered by the digital image collection;   identifying a set of events by analyzing the time series using time-series modeling; and   organizing the plurality of events into an event timeline, such that detected events on an event timeline between the determined set of events are grouped into clusters on the event timeline.   
     
     
         17 . The computer-readable medium of  claim 16 , wherein the detecting the plurality of events comprises detecting the plurality of events based on a selected time granularity. 
     
     
         18 . The computer-readable medium of  claim 17 , wherein selecting the granularity of event detection is based on choosing the fewest detected events that preserve the significant events during a given time period. 
     
     
         19 . The computer-readable medium of  claim 16 , further comprising enabling user browsing of images associated with at least one detected event of the plurality of events. 
     
     
         20 . The computer-readable medium of  claim 16 , further comprising:
 presenting a display of the event timeline; and   receiving a user selection of the event timeline.