IP Library Granted Patent US 12,190,582
Granted Patent B2
US 12,190,582 · App. 18/310,321 · Granted Jan 7, 2025

Automated event detection and photo product creation

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Quick Facts
Patent No.
US 12,190,582
App. No.
18/310,321
Granted
Jan 7, 2025
Kind
B2
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.

Claims (74)

1. A method for automatically detecting events for generating a photo product, the method comprising:

receiving photos captured over a plurality of days from a user computing device;

without user initiation:

automatically identifying an event comprising one or more days of the plurality of days based on daily numbers of the captured photos over the plurality of days, wherein the identified event is associated with at least one subset of the captured photos;

automatically selecting a photo-product design for the identified event, wherein the selected photo-product design defines a total number of photos to be included in the photo-product design;

for each subset of captured photos associated with the identified event, determining a subset weight based on a number of captured photos associated with the subset and a total number of captured photos associated with the identified event;

automatically determining a number of product photos allocated to each subset of the identified event based on a multiplication of the subset weight determined for each subset of the identified event and the total number of product photos to be included in the photo-product design;

automatically selecting product photos from the at least one subset of the captured photos for the identified event according to the number of product photos allocated to each subset of the identified event; and

automatically generating a photo-product design for the identified event including the selected product photos; and

providing the generated photo-product design to a user computer device for display on the user computing device.

2. The method of claim 1 , wherein the photos are captured by a camera that is coupled to or integrated with the user computing device.

3. The method of claim 1 , further comprising:

wherein automatically generating the photo-product design for the identified event comprises:

automatically selecting the photo-product design to be created for the event by automatically selecting a photo-product type, a style, and a layout for the photo-product design; and

inserting the selected product photos into the layout of the photo-product design.

4. The method of claim 1 , further comprising:

automatically determining at least one subset of the captured photos associated with the identified event, including:

analyzing the content in the captured photos, wherein the content includes face images and face models within the captured photos; and

identifying properties associated with the captured photos, wherein the properties include geo location metadata and a time interval associated with the captured photos.

5. The method of claim 1 , wherein the subset weight is determined by the number of captured photos associated with the subset of the captured photos divided by the total number of captured photos associated with the identified event.

6. The method of claim 1 , further comprising:

automatically merging adjacent captured photos in a subset into one or more scenes;

determining a scene weight for the photo-product design based on the 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.

7. The method of claim 6 , 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 subset of the identified event.

8. The method of claim 7 , wherein the number of product photos allocated to each of the one or more scenes is determined by a multiplication of the associated scene weight and the number of product photos allocated to the associated subset.

9. The method of claim 1 , wherein automatically selecting the product photos for each subset of the captured photos associated with the identified event comprises:

ranking the captured photos within the subset; and

automatically selecting the captured photos based on the ranking.

10. The method of claim 9 , wherein the ranking of each captured photo is determined by a score associated with each captured photo, wherein the score is calculated based on a predetermined criterion, including at least one of image quality, significance to a user, redundancy between captured photos, similarity between captured photos, and social relevance.

11. The method of claim 1 , wherein automatically identifying the event comprises:

determining an average number of captured photos per day over the plurality of days; and

comparing a daily number of captured photos over the plurality of days to the average number of captured photos per day over the plurality of days.

12. The method of claim 1 , wherein the event is identified when the daily number of captured photos is at least 50% higher than the average number of captured photos per day.

13. The method of claim 1 , wherein the identified event includes a single day.

14. The method of claim 1 , wherein the identified event includes multiple days.

15. A photo-product design system for automatically detecting events for generating a photo-product, the photo-product design system comprising:

at least one processor; and

at least one memory coupled to the at least one processor and storing instructions that, when executed by the at least one processor, cause the photo-product design system to:

receive photos captured over a plurality of days from a user computing device;

without user initiation:

automatically identify an event comprising one or more days of the plurality of days based on daily numbers of the captured photos over the plurality of days, wherein the identified event is associated with at least one subset of the captured photos;

automatically select a photo-product design for the identified event, wherein the selected photo-product design defines a total number of photos to be included in the photo-product design;

for each subset of captured photos associated with the identified event, determine a subset weight based on a number of captured photos associated with the subset and a total number of captured photos associated with the identified event;

automatically determine a number of product photos allocated to each subset of the identified event based on a multiplication of the subset weight determined for each subset of the identified event and the total number of product photos to be included in the photo-product design;

automatically select product photos from the at least one subset of the captured photos for the identified event according to the number of product photos allocated to each subset of the identified event; and

automatically generate a photo-product design for the identified event including the selected product photos; and

provide the generated photo-product design to a user computer device for display on the user computing device.

16. The photo-product design system of claim 15 , wherein to automatically generate a photo-product design for the identified event, the photo-product design system is further caused to, without user initiation:

automatically select the photo-product design to be created for the event by automatically selecting a photo-product type, a style, and a layout for the photo-product design; and

insert the selected product photos into the layout of the photo-product design.

17. The photo-product design system of claim 15 , wherein the photo-product design system is further caused to:

automatically determine at least one subset of the captured photos associated with the identified event, including:

analyzing the content in the captured photos, wherein the content includes face images and face models within the captured photos; and

identifying properties associated with the captured photos, wherein the properties include geo location metadata and a time interval associated with the captured photos.

18. The photo-product design system of claim 15 , wherein the photo-product design system is further caused to:

automatically merge adjacent captured photos in a subset into one or more scenes;

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.

19. The photo-product design system of claim 15 , wherein the photo-product design system is further caused to:

automatically determine an average number of captured photos per day over the plurality of days; and

identify the event by comparing the daily numbers of captured photos over the plurality of days to the average number of captured photos per day over the plurality of days.

20. A computer-readable non-transitory memory storing data that, when executed by a processor of a computer, causes the computer to:

receive photos captured over a plurality of days from a user computing device;

without user initiation:

automatically identify an event comprising one or more days of the plurality of days based on daily numbers of the captured photos over the plurality of days, wherein the identified event is associated with at least one subset of the captured photos;

automatically select a photo-product design for the identified event, wherein the selected photo-product design defines a total number of photos to be included in the photo-product design;

for each subset of captured photos associated with the identified event, determine a subset weight based on a number of captured photos associated with the subset and a total number of captured photos associated with the identified event;

automatically determine a number of product photos allocated to each subset of the identified event based on a multiplication of the subset weight determined for each subset of the identified event and the total number of product photos to be included in the photo-product design;

automatically select product photos from the at least one subset of the captured photos for the identified event according to the number of product photos allocated to each subset of the identified event; and

automatically generate a photo-product design for the identified event including the selected product photos; and

provide the generated photo-product design to a user computer device for display on the user computing device.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 2, 2023
From: AMIR, ROY; AROYO, NIMROD; RIBAK, NADAV; SHALEV, TOMER; HOLLANDER, YANAY
To: SHUTTERFLY, INC.
Reel/Frame 064466/0397 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 2, 2023
From: SHUTTERFLY, INC.
To: SHUTTERFLY, LLC
Reel/Frame 064466/0467 →
SECURITY INTEREST Recorded Jun 13, 2023
From: SHUTTERFLY, LLC
To: WILMINGTON TRUST, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 063934/0366 →