Method for event-based semantic classification

Abstract

A method of automatically classifying images in a consumer digital image collection, includes generating an event representation of the image collection; computing global time-based features for each event within the hierarchical event representation; computing content-based features for each image in an event within the hierarchical event representation; combining content-based features for each image in an event to generate event-level content-based features; and using time-based features and content-based features for each event to classify an event into one of a pre-determined set of semantic categories.

What is claimed is: 
     
         1 . A method comprising:
 generating, using a processor, time-based event boundaries detected in a plurality of images;   computing inter-event durations;   grouping events into clusters based on the inter-event durations; and   validating, using a rule-based system, that each event belongs to an associated cluster based on event level content based features.   
     
     
         2 . The method of  claim 1 , wherein grouping events into clusters includes using density-based clustering. 
     
     
         3 . The method of  claim 1 , wherein the inter-event durations span multiple days. 
     
     
         4 . The method of  claim 1 , wherein the inter-event durations span small duration gaps. 
     
     
         5 . The method of  claim 4 , wherein the small duration gaps are less than 18 hours. 
     
     
         6 . The method of  claim 1 , wherein validating, using a rule-based system, comprises referencing a database of auxiliary factual information associated with subjects identified in the plurality of images. 
     
     
         7 . The method of  claim 1 , further comprising determining a location for each image in an event and grouping events into clusters based upon the locations. 
     
     
         8 . The method of  claim 1 , further comprising determining a subject distance for each image in an event and grouping events into clusters based upon the determined locations. 
     
     
         9 . A system comprising:
 one or more processors configured to:
 generate time-based event boundaries detected in a plurality of images; 
 compute inter-event durations; 
 group events into clusters based on the inter-event durations; and 
 validate, using a rule-based system, that each event belongs to an associated cluster based on event level content based features. 
   
     
     
         10 . The system of  claim 9 , wherein events are grouped into clusters using density-based clustering. 
     
     
         11 . The system of  claim 9 , wherein the inter-event durations span multiple days. 
     
     
         12 . The system of  claim 9 , wherein the inter-event durations span less than 18 hours. 
     
     
         13 . The system of  claim 9 , wherein the validation includes referencing a database of auxiliary factual information associated with subjects identified in the plurality of images. 
     
     
         14 . The system of  claim 9 , wherein the one or more processors are further configured to determine a location for each image in an event and group events into clusters based upon the locations. 
     
     
         15 . A non-transitory computer-readable medium having instructions stored thereon, the instructions comprising:
 instructions to generate time-based event boundaries detected in a plurality of images;   instructions to compute inter-event durations;   instructions to group events into clusters based on the inter-event durations; and   instructions to validate, using a rule-based system, that each event belongs to an associated super-event cluster based on event level content based features.   
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , wherein events are grouped into clusters using density-based clustering. 
     
     
         17 . The non-transitory computer-readable medium of  claim 15 , wherein the inter-event durations span multiple days. 
     
     
         18 . The non-transitory computer-readable medium of  claim 15 , wherein the inter-event durations span less than 18 hours. 
     
     
         19 . The non-transitory computer-readable medium of  claim 15 , wherein the instructions to validate includes instructions to reference a database of auxiliary factual information associated with subjects identified in the plurality of images. 
     
     
         20 . The non-transitory computer-readable medium of  claim 15 , further comprising instructions to determine a location for each image in an event and group events into clusters based upon the locations.