IP Library Granted Patent US 10,740,938
Granted Patent B2
US 10,740,938 · App. 15/830,209 · Granted Aug 11, 2020

Cognitive situation-aware vision deficiency remediation

Inventors: Yuk L. Chan (Rochester, NY); Lawrence A. Clevenger (Rhinebeck, NY); Alain Loiseau (Williston, VT); Deepti M. Naphade (Cupertino, CA)
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
G06T11/60B60K35/00G06F3/011G06T7/90G06T11/001G08G1/0962H04L67/02H04L67/306
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Quick Facts
Patent No.
US 10,740,938
App. No.
15/830,209
Granted
Aug 11, 2020
Kind
B2
Abstract

Embodiments include methods, systems, and computer program products for remediating a color vision deficiency. Aspects include receiving a user profile. Aspects also include receiving a real time location image including a plurality of objects. Aspects also include determining an image context. Aspects also include generating a situational notification based at least in part upon the user profile, the real time location image, and the image context.

Claims (34)

1. A computer-implemented method for remediating a vision deficiency, the method comprising:

receiving, by a processor, a user profile, the user profile comprising one or more of a type of vision deficiency and a severity of vision deficiency associated with a user, wherein the user profile is generated during a learning phase, wherein the user profile includes images associated with frequent user locations;

receiving, by the processor, a real time location image comprising a plurality of objects;

determining an image context, wherein the image context comprises a user activity, wherein the user activity comprises driving when the user is in a vehicle and walking when the user is not in a vehicle; and

generating a situational notification based at least in part upon the user profile, the real time location image, and the image context, wherein the situational notification comprises a haptic notification.

2. The computer-implemented method of claim 1 , wherein the situational notification further comprises an audible or visual notification.

3. The computer-implemented method of claim 1 further comprising generating a predictive color replacement specification based at least in part upon the user profile, the real time location image, and the image context.

4. The computer-implemented method of claim 3 , further comprising implementing the predictive color replacement specification as an augmented reality.

5. The computer-implemented method of claim 3 , wherein generating a predictive color replacement specification comprises determining a live road condition based at least in part upon GPS location and user travel direction.

6. The computer-implemented method of claim 3 , wherein the predictive color replacement specification is based at least in part upon an importance level.

7. The computer-implemented method of claim 3 further comprising displaying the predictive color replacement specification as an overlay on a windshield or an eyeglass lens.

8. The computer-implemented method of claim 1 , further comprising assigning an importance level to each of the plurality of objects based at least in part upon the image context.

9. The computer-implemented method of claim 1 , wherein the image context comprises a location classification or a user preference.

10. The computer-implemented method of claim 1 comprising receiving a live road condition.

11. The computer-implemented method of claim 1 , wherein the user profile comprises a type of color vision deficiency.

12. A processing system for remediating a vision deficiency, comprising:

a processor in communication with one or more types of memory, the processor configured to:

receive a user profile, the user profile comprising one or more of a type of vision deficiency and a severity of vision deficiency associated with a user, wherein the user profile is generated during a learning phase, wherein the user profile includes images associated with frequent user locations;

receive a real time location image comprising a plurality of objects;

determine an image context, wherein the image context comprises a user activity, wherein the user activity comprises driving when the user is in a vehicle and walking when the user is not in a vehicle; and

generate a situational notification based at least in part upon the user profile, the real time location image, and the image context, wherein the situational notification comprises a haptic notification.

13. The processing system of claim 12 , wherein the processor is configured to generate a predictive color replacement specification based at least in part upon the user profile, the real time location image, and the image context.

14. The processing system of claim 13 , wherein the processor is configured to implement the predictive color replacement specification as an augmented reality.

15. The processing system of claim 13 , wherein determining a predictive color replacement specification comprises determining a live road condition based at least in part upon GPS location and user travel direction.

16. The processing system of claim 13 , wherein the predictive color replacement specification is based at least in part upon an importance level.

17. The processing system of claim 12 , wherein the image context comprises a location classification or a user preference.

18. The processing system of claim 12 , wherein the processor is configured to receive a live road condition.

19. The processing system of claim 12 , wherein the user profile comprises a type of color vision deficiency.

20. A computer program product for remediating a vision deficiency, the computer program product comprising:

a computer readable storage medium readable by a processing circuit and storing program instructions for execution by the processing circuit for performing a method comprising:

receiving a user profile, the user profile comprising one or more of a type of vision deficiency and a severity of vision deficiency associated with a user, wherein the user profile is generated during a learning phase, wherein the user profile includes images associated with frequent user locations;

receiving a real time location image comprising a plurality of objects;

determining an image context, wherein the image context comprises a user activity, wherein the user activity comprises driving when the user is in a vehicle and walking when the user is not in a vehicle; and

generate a situational notification based at least in part upon the user profile, the real time location image, and the image context, wherein the situational notification comprises a haptic notification.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 6, 2019
From: CHAN, YUK L.; CLEVENGER, LAWRENCE A.; LOISEAU, ALAIN; NAPHADE, DEEPTI
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 049970/0573 →
Continuity (1)
Related Publication 20190172234A1 · Jun 6, 2019
Cited By (1)
US 12,738,072