Automated event detection and photo product creation

Abstract

A computer-implemented method for automatically detecting events and creating photo-product designs based on the events in a photo-product design system includes automatically identifying an event by an event detection module based on daily numbers of captured photos over a plurality of days, automatically selecting a photo-product type by an intelligent product design creation engine in the photo-product design system, calculating a daily weight for a photo product design in the photo-product type based on the daily numbers of captured photos, automatically determining a number of product photos allocated to each day based on associated daily weight, automatically selecting product photos from the captured photos each day at the event according to the number of product photos allocated to each day, and automatically creating a photo-product design for the event using the selected product photos.

What is claimed is: 
     
         1 . A computer-implemented method for automatically detecting events and creating photo-product designs based on the events, comprising:
 in a photo-product design system, automatically identifying an event by an event detection module based on daily numbers of captured photos over a plurality of days;   automatically selecting a photo-product type by an intelligent product design creation engine in the photo-product design system;   calculating a daily weight for a photo product design in the photo-product type based on the daily numbers of captured photos;   automatically determining a number of product photos allocated to each day based on associated daily weight;   automatically selecting product photos from the captured photos each day at the event according to the number of product photos allocated to each day; and   automatically creating a photo-product design for the event using the selected product photos.   
     
     
         2 . The computer-implemented method of  claim 1 , wherein the daily weight is determined by an associated daily number of captured photos divided by a total number of captured photos in the event. 
     
     
         3 . The computer-implemented method of  claim 1 , wherein the number of product photos allocated to each day in the event is determined by a product of the associated daily weight and a total number of captured photos in the event. 
     
     
         4 . The computer-implemented method of  claim 1 , further comprising:
 automatically merging adjacent captured photos in a day into one or more scenes;   calculating a scene weight for the photo product design based on numbers of captured photos in the one or more scenes;   automatically determining a number of product photos allocated to each of the one or more scenes based on associated scene weight; and   automatically selecting product photos from the captured photos at each of the one or more scenes according to the number of product photos allocated to each of the one or more scenes.   
     
     
         5 . The computer-implemented method of  claim 4 , wherein the scene weight is determined by a number of captured photos of an associated scene divided by a total number of captured photos in an associated day in the event. 
     
     
         6 . The computer-implemented method of  claim 4 , wherein the number of product photos allocated to each of the one or more scenes is determined by a product of the associated scene weight and a total number of captured photos in the associated day. 
     
     
         7 . The computer-implemented method of  claim 1 , further comprising:
 automatically selecting a product style for the photo-product design by the intelligent product design creation engine.   
     
     
         8 . The computer-implemented method of  claim 1 , further comprising:
 automatically selecting a product layout for the photo-product design by the intelligent product design creation engine.   
     
     
         9 . The computer-implemented method of  claim 1 , wherein the step of automatically selecting product photos from the captured photos comprises:
 ranking the captured photos; and   automatically selecting the product photos from the captured photos based on the ranking of the captured photos.   
     
     
         10 . The computer-implemented method of  claim 1 , wherein the step of automatically identifying an event by an event detection module comprises:
 determining an average number of captured photos per day; and   identifying the event by the event detection module by comparing daily numbers of captured photos over the plurality of days to the average number of captured photos per day.   
     
     
         11 . The computer-implemented method of  claim 10 , wherein the event is identified by the event detection module when a daily number of captured photos is at least 50% higher than the average number of captured photos per day. 
     
     
         12 . The computer-implemented method of  claim 1 , wherein the event includes a single day. 
     
     
         13 . The computer-implemented method of  claim 1 , wherein the event includes multiple days 
     
     
         14 . A photo-product design system for automatically detecting events and creating photo-product designs for the events, comprising:
 an event detection module configured to automatically identify an event based on daily numbers of captured photos over a plurality of days; and   an intelligent product design creation engine configured to automatically select a photo-product type, to calculate a daily weight for a photo product design in the photo-product type based on the daily numbers of captured photos, automatically determine a number of product photos allocated to each day based on associated daily weight, automatically select product photos from the captured photos each day at the event according to the number of product photos allocated to each day, and automatically create a photo-product design for the event using the selected product photos.   
     
     
         15 . The photo-product design system of  claim 14 , wherein the intelligent product design creation engine is configured to automatically merge adjacent captured photos in a day into one or more scenes, to calculate a scene weight for the photo product design based on numbers of captured photos in the one or more scenes, automatically determine a number of product photos allocated to each of the one or more scenes based on associated scene weight, and automatically select product photos from the captured photos at each of the one or more scenes according to the number of product photos allocated to each of the one or more scenes. 
     
     
         16 . The photo-product design system of  claim 14 , wherein the intelligent product design creation engine is configured to automatically select a product style for the photo-product design and to select a product layout for the photo-product design. 
     
     
         17 . The photo-product design system of  claim 14 , wherein the intelligent product design creation engine is configured to automatically rank the captured photos and to select the product photos from the captured photos based on the ranking of the captured photos. 
     
     
         18 . The photo-product design system of  claim 14 , wherein the event detection module is configured to automatically determine an average number of captured photos per day, and identify the event by comparing daily numbers of captured photos over the plurality of days to the average number of captured photos per day. 
     
     
         19 . The photo-product design system of  claim 14 , wherein the event includes a single day. 
     
     
         20 . The photo-product design system of  claim 14 , wherein the event includes multiple days.