RECOMMENDING TRANSFORMATIONS FOR PHOTOGRAPHY

• US 20160100101A1
• Filed: 10/05/2015
• Published: 04/07/2016
• Est. Priority Date: 12/21/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: COHEN, Richard Zarek, HAMILTON, Robert William
• Granted Patent: US 9,438,791 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 11/60 Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/20024 Filtering details
• CPC Class Codes: H04N 13/122 Improving the 3D impression of stereoscopic images by modifying image signal contents, e.g. by filtering or adding monoscopic depth cues H04N13/128 takes precedence
• CPC Class Codes: H04N 19/117 Filters, e.g. for pre-processing or post-processing sub-band filter banks H04N19/635
• CPC Class Codes: H04N 21/4545 Input to filtering algorithms, e.g. filtering a region of the image
• CPC Class Codes: H04N 23/632 for displaying or modifying preview images prior to image capturing, e.g. variety of image resolutions or capturing parameters
• CPC Class Codes: H04N 23/64 Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
• CPC Class Codes: H04N 23/661 Transmitting camera control signals through networks, e.g. control via the Internet
• CPC Class Codes: H04N 5/2621 Cameras specially adapted for the electronic generation of special effects during image pickup, e.g. digital cameras, camcorders, video cameras having integrated special effects capability

Abstract

A method, computer program product, and system is described. An aspect of an image is identified. One or more other images are identified based upon, at least in part, the one or more other images including one or more other aspects similar to the identified aspect of the image. One or more image filters associated with the one or more other images, including a first image filter, are identified. The first image filter is applied to the image.

Claims

1. (canceled)

2. A computer-implemented method comprising:

identifying a first aspect of a captured image;

identifying a reference image based, at least in part, on a second aspect of the reference image that is same as, or like, the first aspect of the captured image;

analyzing the captured image and the reference image to determine a second feature of the reference image corresponding to a first feature of the captured image and the second feature being different from the first feature of the captured image;

identifying one or more image filters to transform the first feature of the captured image to correspond with the second feature of the reference image; and

transforming the captured image by applying the one or more image filters to the captured image.

3. The computer-implemented method of claim 2, wherein identifying the reference image is further based on a popularity associated with the reference image.

4. The computer-implemented method of claim 2, wherein the second feature of the reference image is different from the corresponding first feature of the captured image based, at least in part, on inherent variations during capture.

5. The computer-implemented method of claim 2, wherein analyzing the captured image and the reference image includes comparing a color curve of the captured image and a color curve of the reference image.

6. The computer-implemented method of claim 5, wherein transforming the captured image by applying the image filter causes a decrease in a difference of the color curve of the captured image and the color curve of the reference image.

7. The computer-implemented method of claim 2, further comprising:

providing a recommendation of image filters including the identified one or more image filters, and

receiving a selection of the first image filter from the recommendation of image filters.

8. The computer-implemented method of claim 7, further comprising:

providing a preview of the captured image with representations of effects of at least two of the recommended image filters applied individually on the captured image.

9. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing device, cause the one or more processors to:

identify an object of a captured image;

identify a reference image based, at least in part, on a second object of the reference image that is same as, or like, the object of the captured image;

analyzing the captured image and the reference image to determine a second feature of the reference image corresponding to a first feature of the captured image and the second feature being different from the first feature of the captured image, wherein the second feature is determined based on image data for the reference image;

identify one or more image filters, including a first image filter to transform the first feature of the captured image to correspond with the second feature of the reference image; and

transform the captured image by applying the first image filter to the captured image.

10. The non-transitory computer-readable medium of claim 9, wherein identifying the reference image is further based on a popularity associated with the reference image.

11. The non-transitory computer-readable medium of claim 9, wherein the second feature of the reference image is different from the corresponding first feature of the captured image based, at least in part, on inherent variations during capture.

12. The non-transitory computer-readable medium of claim 9, wherein analyzing the captured image and the reference image includes comparing a color curve of the captured image and a color curve of the reference image.

13. The non-transitory computer-readable medium of claim 12, wherein transforming the captured image by applying the first image filter causes a decrease in difference of the color curve of the captured image and color curve of the reference image.

14. The non-transitory computer-readable medium of claim 9, further comprising:

providing a recommendation of image filters including the identified one or more image filters, and

receiving a selection of the first image filter from the recommendation of image filters.

15. The non-transitory computer-readable medium of claim 14, further comprising providing a preview of the captured image with representations of effects of at least two of the recommended image filters applied individually on the captured image.

16. A system comprising:

one or more processors; and

a memory coupled to the one or more processors, the memory configured to store instructions that upon execution by the one or more processors cause the one or more processors to;

identify a first aspect of a captured image;

identify a reference image based, at least in part, on a second aspect of the reference image that is same as, or like, the first aspect of the captured image;

analyze the captured image and the reference image to determine a second feature corresponding to a first feature of the captured image and the second feature being different from the first feature of the captured image;

identify one or more image filters to transform the first feature of the captured image to correspond with the second feature of the reference image; and

transform the captured image by applying at least one of the one or more image filters to the captured image.

17. The system of claim 16, wherein identifying the reference image is further based on a popularity associated with the reference image.

18. The system of claim 16, wherein the second feature of the reference image is different from the corresponding first feature of the captured image based, at least in part, on inherent variations during capture.

19. The system of claim 16, wherein analyzing the captured image and the reference image includes comparing a color curve of the captured image and a color curve of the reference image.

20. The system of claim 19, wherein transforming the captured image by applying the at least one of the one or more image filters causes a decrease in difference of the color curve of the captured image and color curve of the reference image.

21. The system of claim 16, further comprising:

providing a recommendation of image filters including the identified one or more image filters, and

receiving a selection of the at least one of the one or more image filters from the recommendation of image filters.