Dynamic contextual video capture

• US 10,338,407 B2
• Filed: 06/26/2017
• Issued: 07/02/2019
• Est. Priority Date: 06/26/2017
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Bostick, James E., Ganci, Jr., John M., Keen, Martin G., O'Connell, Brian M.
• Primary Examiner(s): Allen, Stephone B
• Assistant Examiner(s): Fissel, Travis S
• Application Number:
  US15/632,835
• Publication Number:
  US 20180373058A1
• Time in Patent Office: 736 Days
• Field of Search: 35115901-15903, 35115939, 351178, 386224, 386228, 706 16, 706 21, 348115, 348E13036, 348E13041, 348E13048-E13052
• CPC Class Codes: G02C 7/04 Contact lenses for the eyes disinfection or sterilisation of contact lenses A61L12/00
• CPC Class Codes: G03B 17/38 Releasing-devices separate from shutter integral with shutter G03B9/08
• CPC Class Codes: G03B 17/48 adapted for combination with other photographic or optical apparatus
• CPC Class Codes: H04N 23/50 Constructional details
• CPC Class Codes: H04N 23/57 Mechanical or electrical details of cameras or camera modules specially adapted for being embedded in other devices

Abstract

Embodiments of the present invention provide a method, computer program product and system for dynamic video capture through a contact lens based on dynamic contextual identification. Initially, a set of identifying information and a video stream from a contact lens is received. A determination is made as to whether to capture the video stream, based on the received information. The determining to capture the video stream is based on, at least one of, the user interest level exceeding a threshold and detecting a contextual identifier within the received the video stream from a contact lens. Responsive to determining to capture the video stream, the video stream is classified into a category and saving based on the classification category of the video stream.

Claims

1. A method comprising:

receiving, by one or more processors, a set of identifying information and a video stream from a contact lens;

determining, by one or more processors, whether to capture the video stream, wherein determining whether to capture the video stream is based on, at least one of, the user interest level exceeding a threshold and detection of a contextual identifier within the received video stream from the contact lens;

classifying, by one or more processors, the video stream into a category;

responsive to determining to capture the video stream, saving, by one or more processors, the video stream based on the classification category of the video stream; and

creating, by one or more processors, a new contextual identifier, wherein creating a new contextual identifier comprises;

identifying, by one or more processors, at least two incidences of the user deleting the saved video stream, subsequent to the saving the video stream, within a predetermined time,

deriving, by one or more processors, at least one common person, object, place and activity within each of the identified incidences, and

responsive to deriving at least one common person, object, place and activity within each of the identified incidences, determining, by one or more processors, a habitual pattern of the user deleting the saved video stream, subsequent to the saving of the video stream.

2. The method of claim 1, wherein the contextual identifier is one or more predefined person, object, place and activity.

3. The method of claim 1, further comprises:

determining, by one or more processors, the user interest level, based on biometric data of the user, wherein;

the biometric data of the user is received from the set of identifying information, and

determining the user interest level comprises detecting, by one or more processors, at least one of;

a change in the user'"'"'s pupil dilation;

a change in the user'"'"'s heart rate; and

a change in the user'"'"'s facial expression.

4. The method of claim 1, wherein detecting the contextual identifier comprises:

analyzing, by one or more processors, the received video stream from the contact lens; and

applying, by one or more processors, at least one audio/video recognition system, wherein the at least one audio/video recognition system searches the received video stream for a predefined person, a predefined object, a predefined place, a predefined activity, and a predefined audible clip.

5. The method of claim 1, wherein classifying the video stream into a category, further comprises:

establishing, by one or more processors, at least two categories, wherein a first category is public and the second category is private; and

determining, by one or more processors, a pattern wherein the pattern is;

of the user placing the video stream into one of the at least two categories, and

based on deriving, by one or more processors, at least one common person, object, place and activity within each category.

6. The method of claim 1, further comprising:

determining, by one or more processors, not to capture the video stream, wherein determining not to capture the video stream is based on, at least one of, the user interest level below a threshold and detecting a second contextual identifier within the received the video stream from a contact lens, wherein the second contextual identifier is classified as restricted.

7. A computer program product comprising:

a computer readable storage medium and program instructions stored on the computer readable storage medium, the program instructions comprising;

program instructions to receive a set of identifying information and a video stream from a contact lens;

program instructions to determine whether to capture the video stream, wherein the program instructions to determine whether to capture the video stream is based on, at least one of, the user interest level exceeding a threshold and detection of a contextual identifier within the received video stream from the contact lens;

program instructions to classify the video stream into a category;

responsive to determining to capture the video stream, program instructions to save the video stream based on the classification category of the video stream; and

program instructions to create a new contextual identifier, where the program instructions to create a new contextual identifier comprise;

program instructions to identify at least two incidences of the user deleting the saved video stream, subsequent to the saving the video stream, within a predetermined time,

program instructions to derive at least one common person, object, place and activity within each of the identified incidences, and

responsive to deriving at least one common person, object, place and activity within each of the identified incidences, program instructions to determine a habitual pattern of the user deleting the saved video stream, subsequent to the saving of the video stream.

8. The computer program product of claim 7, wherein the contextual identifier is one or more predefined person, object, place and activity.

9. The computer program product of claim 7, further comprising:

program instructions to determine the user interest level, based on biometric data of the user, wherein;

the biometric data of the user is received from the set of identifying information, and

the program instructions to determining the user interest level comprise;

program instructions to detect at least one of;

a change in the user'"'"'s pupil dilation;

a change in the user'"'"'s heart rate; and

a change in the user'"'"'s facial expression.

10. The computer program product of claim 7, wherein the program instructions to detect the contextual identifier comprise:

program instructions to analyze the received video stream from the contact lens; and

program instructions to apply at least one audio/video recognition system, wherein the at least one audio/video recognition system searches the received video stream for a predefined person, a predefined object, a predefined place, a predefined activity, and a predefined audible clip.

11. The computer program product of claim 7, wherein the program instructions to classify the video stream into a category, further comprise:

program instructions to establish at least two categories, wherein a first category is public and the second category is private; and

program instructions to determine a pattern wherein the pattern is;

of the user placing the video stream into one of the at least two categories, and

based on program instructions to derive at least one common person, object, place and activity within each category.

12. The computer program product of claim 7, further comprising:

program instructions to determine not to capture the video stream, wherein determining not to capture the video stream is based on, at least one of, the user interest level below a threshold and detecting a second contextual identifier within the received the video stream from a contact lens, wherein the second contextual identifier is classified as restricted.

13. A computer system comprising:

one or more computer processors;

one or more computer readable storage media;

program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising;

program instructions to receive a set of identifying information and a video stream from a contact lens;

program instructions to determine whether to capture the video stream, wherein the program instructions to determine to capture the video stream is based on, at least one of, the user interest level exceeding a threshold and detection of a contextual identifier within the received video stream from the contact lens;

program instructions to classify the video stream into a category;

responsive to determining to capture the video stream, program instructions to save the video stream based on the classification category of the video stream; and

program instructions to create a new contextual identifier, where the program instructions to create a new contextual identifier comprise;

program instructions to identify at least two incidences of the user deleting the saved video stream, subsequent to the saving the video stream, within a predetermined time,

program instructions to derive at least one common person, object, place and activity within each of the identified incidences, and

responsive to deriving at least one common person, object, place and activity within each of the identified incidences, program instructions to determine a habitual pattern of the user deleting the saved video stream, subsequent to the saving of the video stream.

14. The computer system of claim 13, wherein the contextual identifier is one or more predefined person, object, place and activity.

15. The computer system of claim 13, further comprising:

program instructions to determine the user interest level, based on biometric data of the user, wherein;

the biometric data of the user is received from the set of identifying information, and

wherein the program instructions to determine the user interest level comprise;

program instructions to detect at least one of;

a change in the user'"'"'s pupil dilation;

a change in the user'"'"'s heart rate; and

a change in the user'"'"'s facial expression.

16. The computer system of claim 13, wherein the program instructions to detect the contextual identifier comprise:

program instructions to analyze the received video stream from the contact lens;

program instructions to apply at least one audio/video recognition system, wherein the at least one audio/video recognition system searches the received video stream for a predefined person, a predefined object, a predefined place, a predefined activity, and a predefined audible clip.

17. The computer system of claim 13, wherein the program instructions to classify the video stream into a category, further comprise:

program instructions to establish at least two categories, wherein a first category is public and the second category is private; and

program instructions to determine a pattern wherein the pattern is;

of the user placing the video stream into one of the at least two categories, and

based on program instructions to derive at least one common person, object, place and activity within each category.