METHODS, SYSTEMS, AND DEVICES FOR HANDLING INSERTED DATA INTO CAPTURED IMAGES

• US 20150106194A1
• Filed: 12/16/2013
• Published: 04/16/2015
• Est. Priority Date: 10/10/2013
• Status: Active Grant

• Current Assignee: Elwha LLC (Intellectual Ventures LLC)
• Original Assignee: Elwha LLC (Intellectual Ventures LLC)
• Inventors: Holman, Pablos, Hyde, Roderick A., Levien, Royce A., Lord, Richard T., Lord, Robert W., Malamud, Mark A.
• Granted Patent: US 10,102,543 B2
• Time in Patent Office: Days
• US Class Current: 705/14.46
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06Q 30/0247 Calculate past, present or future revenues
• CPC Class Codes: G06T 7/00 Image analysis
• CPC Class Codes: H04N 1/00244 with a server, e.g. an internet server fax-servers or the like for store and forward H04N1/324

Abstract

Computationally implemented methods and systems include acquiring a captured image, wherein the captured image depicts at least one entity, performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image, and modifying the captured image by placing at least one advertisement image at a particular location of the captured image. In addition to the foregoing, other aspects are described in the claims, drawings, and text.

Claims

1. A computationally-implemented method, comprising:

acquiring a captured image, wherein the captured image depicts at least one entity;

performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image;

modifying the captured image by placing at least one advertisement image at a particular location of the captured image; and

calculating an updated estimated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location.

6. The computationally-implemented method of claim 1, wherein said acquiring a captured image, wherein the captured image depicts at least one entity comprises:

acquiring the captured image from an image capture device, wherein the captured image depicts at least one entity.

7. The computationally-implemented method of claim 6, wherein said acquiring the captured image from an image capture device, wherein the captured image depicts at least one entity comprises:

receiving the captured image from a wearable computer that is configured to covertly capture one or more images, wherein the captured image depicts at least one entity.

8. The computationally-implemented method of claim 1, wherein said acquiring a captured image, wherein the captured image depicts at least one entity comprises:

receiving the captured image from a server, wherein the captured image depicts at least one entity.

9. The computationally-implemented method of claim 8, wherein said receiving the captured image from a server, wherein the captured image depicts at least one entity comprises:

receiving the captured image from the server that has performed one or more processes on the image, wherein the captured image depicts at least one entity.

10. The computationally-implemented method of claim 9, wherein said receiving the captured image from the server that has performed one or more processes on the image, wherein the captured image depicts at least one entity comprises:

receiving the captured image from the server that has determined that a potential revenue generated from the captured image is less than a potential liability incurred from a distribution of the captured image, wherein the captured image depicts at least one entity.

11. The computationally-implemented method of claim 1, wherein said acquiring a captured image, wherein the captured image depicts at least one entity comprises:

acquiring the captured image that has previously been encrypted, wherein the captured image depicts at least one entity.

14. The computationally-implemented method of claim 11, wherein said acquiring the captured image that has previously been encrypted, wherein the captured image depicts at least one entity comprises:

acquiring the captured image that has previously been encrypted through use of a unique device code associated with an image capture device configured to capture the captured image.

15. The computationally-implemented method of claim 1, wherein said acquiring a captured image, wherein the captured image depicts at least one entity comprises:

acquiring the captured image that contains a privacy beacon, wherein the captured image depicts at least one entity.

17. The computationally-implemented method of claim 15, wherein said acquiring the captured image that contains a privacy beacon, wherein the captured image depicts at least one entity comprises:

acquiring the captured image that contains a privacy beacon configured to be used to obtain data that regards the entity depicted in the captured image.

18. The computationally-implemented method of claim 17, wherein said acquiring the captured image that contains a privacy beacon configured to be used to obtain data that regards the entity depicted in the captured image comprises:

acquiring the captured image that contains the privacy beacon configured to be used to obtain term data that includes one or more terms of service that govern distribution of the captured image.

20. The computationally-implemented method of claim 1, wherein said performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image comprises:

performing the comparison between an estimated potential revenue generated from the distribution of the captured image to a social networking site, and an estimated potential liability incurred for the distribution of the captured image.

21. The computationally-implemented method of claim 1, wherein said performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image comprises:

determining whether the estimated potential revenue generated from a direct sale of the captured image is greater than the estimated potential liability incurred for the distribution of the captured image.

23. The computationally-implemented method of claim 1, wherein said performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image comprises:

estimating a revenue value that corresponds to an estimated potential advertisement revenue generated from a distribution of the captured image;

obtaining an estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image; and

performing a comparison between the obtained estimated damage value and the estimated revenue value.

24. The computationally-implemented method of claim 1, wherein said performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image comprises:

estimating a revenue value that corresponds to the estimated potential advertisement revenue generated from a distribution of the captured image; and

performing a comparison between the estimated revenue value and the estimated potential liability incurred for distribution of the captured image.

25. The computationally-implemented method of claim 24, wherein said estimating a revenue value that corresponds to the estimated potential advertisement revenue generated from a distribution of the captured image comprises:

estimating the revenue value that corresponds to the estimated potential advertisement revenue generated from a post of the captured image to a social networking site.

32. The computationally-implemented method of claim 1, wherein said performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image comprises:

obtaining an estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image; and

performing a comparison between the estimated damage value and the estimated potential revenue generated from the distribution of the captured image.

33. The computationally-implemented method of claim 32, wherein said obtaining an estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image comprises:

obtaining the estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image at least partly based on term data that includes one or more terms of service that govern the distribution of the image.

35. The computationally-implemented method of claim 32, wherein said obtaining an estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image comprises:

obtaining the estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image at least partly based on privacy metadata related to the captured image.

36. The computationally-implemented method of claim 35, wherein said obtaining the estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image at least partly based on privacy metadata related to the captured image comprises:

obtaining the estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image at least partly based on privacy metadata that identifies the entity depicted in the captured image.

37. The computationally-implemented method of claim 32, wherein said obtaining an estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image comprises:

obtaining a privacy metadata related to the captured image; and

generating an estimated damage value that corresponds to the estimated potential liability incurred for distribution of the captured image, at least partly based on the obtained privacy metadata.

38. The computationally-implemented method of claim 37, wherein said obtaining a privacy metadata related to the captured image comprises:

obtaining a privacy metadata related to a privacy beacon associated with the entity depicted in the captured image.

39. The computationally-implemented method of claim 38, wherein said obtaining a privacy metadata related to a privacy beacon associated with the entity depicted in the captured image comprises:

obtaining the privacy metadata related to a privacy beacon associated with the depicted entity and that was detected in the captured image.

41. The computationally-implemented method of claim 37, wherein said obtaining a privacy metadata related to the captured image comprises:

obtaining the privacy metadata that is configured to facilitate retrieval of term data that regards the entity depicted in the captured image.

44. The computationally-implemented method of claim 41, wherein said obtaining the privacy metadata that is configured to facilitate retrieval of term data that regards the entity depicted in the captured image comprises:

obtaining the privacy metadata that is configured to facilitate retrieval of term data that includes one or more terms of service regarding distribution of the captured image that depicts the entity.

45. The computationally-implemented method of claim 1, wherein said performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image comprises:

estimating an advertisement revenue value that corresponds to the estimated potential advertisement revenue generated from the distribution of the captured image with an advertisement placed in the captured image; and

performing a comparison between the estimated advertisement revenue value and the estimated potential liability incurred for distribution of the captured image.

46. The computationally-implemented method of claim 45, wherein said estimating an advertisement revenue value that corresponds to the estimated potential advertisement revenue generated from the distribution of the captured image with an advertisement placed in the captured image comprises:

estimating the advertisement revenue value that corresponds to the estimated potential advertisement revenue generated from the distribution of the captured image with the advertisement placed in the captured image at a position away from the depicted entity.

47. The computationally-implemented method of claim 1, wherein said modifying the captured image by placing at least one advertisement image at a particular location of the captured image comprises:

modifying the captured image by placing the at least one advertisement image at the particular location of the captured image, wherein the particular location of the at least one advertisement image is at least partially based on the performed comparison.

48. The computationally-implemented method of claim 47, wherein said modifying the captured image by placing the at least one advertisement image at the particular location of the captured image, wherein the particular location of the at least one advertisement image is at least partially based on the performed comparison comprises:

modifying the captured image by placing at least one advertisement image at the particular location of the captured image, wherein the particular location of the at least one advertisement image is at least partially based on a result of the performed comparison.

49. The computationally-implemented method of claim 47, wherein said modifying the captured image by placing the at least one advertisement image at the particular location of the captured image, wherein the particular location of the at least one advertisement image is at least partially based on the performed comparison comprises:

modifying the captured image by placing the at least one advertisement image at the particular location of the captured image, wherein a distance from the particular location to a center of the captured image is proportional to a size of the comparison between the estimated potential revenue and the estimated potential liability.

53. The computationally-implemented method of claim 1, wherein said modifying the captured image by placing at least one advertisement image at a particular location of the captured image comprises:

modifying the captured image by placing at least one advertisement image at a particular location that covers the depicted entity in the captured image, when the estimated potential liability is greater than a particular amount.

55. The computationally-implemented method of claim 1, wherein said modifying the captured image by placing at least one advertisement image at a particular location of the captured image comprises:

modifying the captured image by placing at least one advertisement image at a particular location that overlaps the depicted entity in the captured image.

58. The computationally-implemented method of claim 1, wherein said modifying the captured image by placing at least one advertisement image at a particular location of the captured image comprises:

modifying the captured image by placing a removable advertisement image at the particular location of the captured image.

65. The computationally-implemented method of claim 1, wherein said calculating an updated estimated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location comprises:

estimating an updated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location.

66. The computationally-implemented method of claim 65, wherein said estimating an updated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location comprises:

estimating the updated potential revenue from the modified captured image that includes the at least one advertisement image through estimation of a number of clicks on the at least one advertisement image.

71. The computationally-implemented method of claim 1, wherein said calculating an updated estimated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location comprises:

receiving the updated estimated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location, from a remote location.

72. The computationally-implemented method of claim 1, wherein said calculating an updated estimated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location comprises:

calculating the updated estimated potential revenue from the modified captured image that includes the at least one advertisement image, at least partly based on term data associated with the entity depicted in the captured image.

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74. A computationally-implemented system, comprising:

circuitry for acquiring a captured image, wherein the captured image depicts at least one entity;

circuitry for performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image;

circuitry for modifying the captured image by placing at least one advertisement image at a particular location of the captured image; and

circuitry for calculating an updated estimated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location.

75-145. -145. (canceled)

146. A computer program product, comprising:

a signal-bearing medium bearing;

one or more instructions for acquiring a captured image, wherein the captured image depicts at least one entity;

one or more instructions for performing a comparison between an estimated potential revenue generated from a distribution of the captured image and an estimated potential liability incurred for the distribution of the captured image;

one or more instructions for modifying the captured image by placing at least one advertisement image at a particular location of the captured image; and

one or more instructions for calculating an updated estimated potential revenue from the modified captured image that includes the at least one advertisement image at the particular location.

147. (canceled)