Method of selecting important digital images
A method for selecting important digital images in a collection of digital images, comprising: analyzing the digital images in the collection of digital images to identify one or more sets of similar digital images; identifying one or more sets of similar digital images having the largest number of similar digital images; selecting one or more digital images from the identified largest sets of similar digital images to be important digital images; and storing an indication of the selected important digital image in a processor accessible memory.
1. A method of determining image importance comprising:
analyzing, via a processor of an electronic device, a plurality of digital images stored on a computer memory;
identifying, via the processor, a plurality of similar images from the plurality of digital images
receiving, via the processor, user-designated ratings for each of the plurality of similar images;
determining, via the processor, a qualitative image quality value for each of the plurality of similar images;
determining, via the processor, an aesthetic image quality value for each of the plurality of similar images;
evaluating, via the processor, a utilization pattern for each of the plurality of similar images;
determining, via the processor, one or more important images from the plurality of similar images from a weighted combination of the user-designated ratings, the qualitative image quality values, the aesthetic image quality values, and the utilization patterns of the plurality of similar images; and
storing the one or more important images or identification information of the one or more important images along with information about a relative importance of the one or more important images in a metadata of the one or more important images or as an object in a database.
2. The method of claim 1 wherein the utilization patterns are weighted based on the type of usage of the plurality of similar image.
3. The method of claim 1 wherein the user-designated ratings comprise a “favorites” or “star rating” mechanism.
4. The method of claim 1 further comprising:
filtering, via the processor, one or more similar images with image quality values less than a threshold image quality level.
5. The method of claim 4 wherein the threshold image quality level is predefined.
6. The method of claim 4 wherein the threshold image quality level is adjusted adaptively to include a desired number of digital images in the one or more important images.
7. The method of claim 1 wherein the plurality of similar images is based on similarity in visual appearance, image classification similarity, event clustering, capture location similarity, capture time similarity, capture sequence order, or recurring time intervals.
8. The method of claim 1 , wherein identifying the plurality of similar images further comprises:
identifying, by the processor, images containing persons that are closely related to a reference individual by using automatic face recognition or by manual identification.
9. The method of claim 8 wherein the weighted combination further comprises:
a social relationship between the reference individual and persons included in the digital images.
10. The method of claim 1 wherein the qualitative image quality value relates to image attributes comprising sharpness, image noise, image colorfulness, or image contrast.
11. The method of claim 1 further comprising:
displaying, via the processor, each of the one or more important images on a Graphic User Interface (GUI).
12. The method of claim 11 wherein the one or more important images are displayed according to a relative level of importance.
13. The method of claim 12 wherein the GUI is reordered based on updated levels of importance of the one or more important images.
14. The method of claim 1 wherein the plurality of similar images is a largest subset of the plurality of digital images.
15. The method of claim 14 wherein the largest subset of the plurality of digital images is greater than a pre-defined threshold.
16. The method of claim 1 further comprising:
designating, by the processor, an image with a highest importance value.
17. The method of claim 16 further comprising:
displaying, by the processor, a rendering of a photographic product with the image with the highest importance value on an electronic device.
18. The method of claim 1 further comprising:
assigning, by the processor, an image importance value to each of the plurality of similar images.
19. The method of claim 18 wherein the assigned image importance values are stored in a processor accessible memory.
20. The method of claim 1 wherein the aesthetic image quality values are based on facial presentations within the plurality of similar images.