Automated memory book creation
Embodiments of a system and method for automatic creation of a multimedia presentation or highlight collection from a collection of candidate contents are generally described herein. In some embodiments, each one of a plurality of videos or images in the candidate contents are automatically evaluated for quality, content, metadata, and desirability based on user specified inclusion factors. Inclusion factors may be utilized to generate one or more scores for the candidate contents, which provide for automatic ranking of the candidate contents. Based on scores generated from the selected inclusion factor criteria a highlight collection of images is automatically generated. The highlight collection can be included in a multimedia presentation, in the form of a memory book, slideshow, or digital narrative, and can be automatically generated from the plurality of videos or images.
1. At least one non-transitory machine-readable medium comprising a plurality of instructions that in response to being executed on a computing device, cause the computing device to:
receive a plurality of images;
present a user interface, the user interface including a plurality of inclusion factors, the inclusion factors including the presence or importance of a human being;
receive a criteria, via the user interface, prioritizing at least one of the plurality of inclusion factors;
inspect each one of the plurality of images for the plurality of inclusion factors;
determine an identity of at least one human being in at least one of the plurality of images;
evaluate a level of importance of the at least one human being identified in the at least one of the plurality of images based at least in part on data obtained from a social networking system coupled to the computing device;
determine a score for each one of the plurality of images based on the inspection of the images for the plurality of inclusion factors;
rank the plurality of images according to the score determined for each one of the plurality of images; and
generate a highlight collection including a subset of the plurality of images based on the criteria prioritizing the plurality of images.
2. The at least one non-transitory machine-readable medium as recited in claim 1 , wherein the level of importance is based on a presence of the identified human being in a local database of images.
3. The at least one non-transitory machine-readable medium as recited in claim 1 , wherein the level of importance is based on a frequency with which the identified human being appears in the plurality of images.
4. The at least one non-transitory machine-readable medium as recited in claim 1 , the plurality of inclusion factors comprising at least two of:
a sharpness quality of an image; an exposure quality of an image; a presence of an animal in an image; a quantity of human beings in an image; an importance of a human being in an image; a geographic location depicted in the image; a geographic location data embedded in an image; a geographic location associated with an image; or an image metadata value.
5. The at least one non-transitory machine-readable medium as recited in claim 1 , wherein the instruction to generate the highlight collection include instructions to acquire multimedia content, associated with the subset of the plurality of images, from a database.
6. The at least one non-transitory machine-readable medium as recited in claim 1 , the criteria comprising:
a threshold number of images for inclusion in the highlight collection, or
a percentage of images for inclusion in the highlight collection.
7. A method for automatic creation of a highlight collection by a computer system comprising:
receiving a plurality of images at the computer system;
presenting a user interface, the user interface including a plurality of inclusion factors, the inclusion factors including a presence or importance of a human being;
receiving a criteria, via the user interface, prioritizing at least one of the plurality of inclusion factors;
inspecting each one of the plurality of images with the computer system for the plurality of inclusion factors;
determining an identity of at least one human being in at least one of the plurality of images;
evaluating a level of importance of the at least one human being identified in the at least one of the plurality of images based at least in part on data obtained from a social networking system coupled to the computer system;
determining a score for each one of the plurality of images based on the inspection of the images for the plurality of inclusion factors by the computer system;
ranking the plurality of images according to the score determined by the computer system for each one of the plurality of images; and
generating the highlight collection including a subset of the plurality of images based on the criteria prioritizing the plurality of images.
8. The method of claim 7 , wherein the level of importance is based on a presence of the identified human being in a local database of images or the data from the social network.
9. The method of claim 8 , wherein the level of importance is based on a frequency with which the identified human being appears in the plurality of images.
10. The method of claim 7 , the plurality of inclusion factors comprising at least two of:
a sharpness quality of an image; an exposure quality of an image; a presence of an animal in an image; a quantity of human beings in an image; an importance of a human being in an image; a geographic location depicted in the image; a geographic location data embedded in an image; a geographic location associated with an image; or an image metadata value.
11. The method of claim 7 , comprising:
generating a map depicting a location associated with each one of the plurality of images included in the highlight collection.
12. The method of claim 7 , wherein generating the highlight collection includes acquiring multimedia content, associated with the subset of the plurality of images, from a database that includes a photo or video repository.
13. The method of claim 8 , the criteria comprising:
a threshold number of images for inclusion in the highlight collection, or
a percentage of images for inclusion in the highlight collection.
14. An automatic highlight collection creation system comprising:
a first processor configured to receive a plurality of images from an image capture device, the first processor being configured to receive a criteria, via a user interface, prioritizing at least one of the plurality of inclusion factors, the inclusion factors including a presence or importance of a human being; determine an identity of at least one human being in at least one of the plurality of images; access a social network to determine an importance of an identified individual in at least one of the plurality of images; and inspect each one of the plurality of images based for the plurality of inclusion factors, and determine a score for each one of the plurality of images based on the inspection of the images for the plurality of inclusion factors;
a second processor configured to receive a subset of the plurality of images, and generate a highlight collection based on the criteria prioritizing at least one of the plurality of inclusion factors, and the score determined for each one of the plurality of images; and
a network coupled to the first processor and the second processor.
15. The system of claim 14 , the plurality of inclusion factors comprising:
a sharpness quality of an image; an exposure quality of an image; a presence of an animal in an image; a quantity of human beings in an image; an importance of a human being in an image; a geographic location depicted in the image; a geographic location data embedded in an image; a geographic location associated with an image; or an image metadata value.
16. The system of claim 14 , wherein
the level of importance is based on a frequency with which the identified human being appears in the plurality of images.
17. The system of claim 14 , wherein the second processor is configured to generate a map depicting a location associated with each one of the plurality of images included in the highlight collection.
18. The system of claim 14 , comprising:
an image database including a plurality of images;
wherein the first processor is configured to access the image database to determine an importance of an identified individual in at least one of the plurality of images.