Computer systems and computer-implemented methods for psychodiagnostics and psycho personality correction using electronic computing device

• US 10,729,368 B1
• Filed: 07/25/2019
• Issued: 08/04/2020
• Est. Priority Date: 07/25/2019
• Status: Active Grant

• Current Assignee: Facemetrics Limited
• Original Assignee: Facemetrics Limited
• Inventors: Boiko, Mikhail, Arol, Aleh, Pirshtuk, Dzianis, Vinahradau, Aliaksandr, Glinsky, Alex, Kavaliou, Pavel
• Primary Examiner(s): Patel, Jayesh A
• Application Number:
  US16/522,186
• Time in Patent Office: 376 Days
• Field of Search: None
• CPC Class Codes: A61B 5/0077 Devices for viewing the surface of the body, e.g. camera, magnifying lens
• CPC Class Codes: A61B 5/167 Personality evaluation
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G06N 3/048 Activation functions
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 3/082 modifying the architecture, e.g. adding, deleting or silencing nodes or connections
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 10/82 using neural networks
• CPC Class Codes: G06V 40/166 using acquisition arrangements
• CPC Class Codes: G06V 40/174 Facial expression recognition
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A computer-implemented method and system can include obtaining, by at least one processor, at least one visual input comprising a face of at least one person. The at least one processor can input the at least one visual input into at least one psychodiagnostic neural network (PNN) to obtain at least one personality metric of the at least one person. The at least one personality metric of the at least one person can include at least one personality dimension and at least one numerical personality score. The at least one numerical personality score may provide a numerical indication of the strength of a particular personality dimension and display at least one personality report on at least one screen of at least one computing device. The at least one personality report may include the at least one personality metric of the at least one person.

Claims

1. A computer-implemented method, comprising:

obtaining, by at least one processor, at least one neural network, obtaining, by the at least one processor, at least one set of visual inputs;

wherein each visual input of the at least one set of visual inputs comprises a face of at least one person;

annotating, by the at least one processor, the at least one set of visual inputs with at least one set of results of at least one personality test, thereby obtaining at least one set of annotated visual inputs;

wherein each annotated visual input of the at least one set of annotated visual inputs comprises;

the face of the at least one person, and

the result of the at least one personality test corresponding to the at least one person;

inputting the at least one set of annotated visual inputs into the at least one neural network, thereby obtaining at least one psychodiagnostic neural network (PNN);

obtaining, by the at least one processor, at least one additional visual input comprising a face of at least one person;

inputting, by the at least one processor, the at least one additional visual input into the at least one PNN, so as to obtain at least one personality metric of the at least one person of the at least one additional visual input;

wherein the at least one personality metric of the at least one person of the at least one additional visual input comprises;

at least one personality dimension of the at least one person of the at least one additional visual input, and

at least one numerical personality score of the at least one person of the at least one additional visual input,

wherein the at least one numerical personality score provides a numerical indication of the strength of the at least one personality dimension; and

displaying at least one personality report on at least one screen of at least one computing device;

wherein the at least one personality report comprises the at least one personality metric of the at least one person of the at least one additional visual input.

2. The method of claim 1, wherein each visual input of the at least one set of visual inputs, the at least one additional visual input, or any combination thereof comprises at least one video frame, at least one image, or both.

3. The method of claim 1, wherein the at least one personality metric is at least one of:

at least one psychotype according to Briggs Myers, at least one personality trait according to the Big 5, a compatibility score, a score evaluating the at least one person in a particular situation, or a combination thereof.

4. The method of claim 1, wherein the at least one personality dimension is at least one of:

extraversion, introversion, sensing, intuition, judging, thinking, feeling, openness, neuroticism, agreeableness, dating, work, interview, friendship, sex, or combinations thereof.

5. The method of claim 1, further comprising, by the at least one processor, displaying at least one personalized recommendation to the at least one screen of the at least one computing device;

wherein the at least one personalized recommendation is based on the at least one personality metric.

6. The method of claim 5, wherein the at least one personalized recommendation is further based on a particular situation.

7. The method of claim 6, wherein the particular situation comprises at least one of:

a date, work, an interview, a party, or combinations thereof.

8. The method of claim 7, further comprising, by the at least one processor:

analyzing at least one of;

the facial expression of the at least one person or the appearance of the at least one person; and

optimizing at least one of;

the facial expression of the at least one person or the appearance of the at least one person for the particular situation.

9. The method of claim 8, wherein an optimal score is indicated by “

1” and

a non-optimal score is indicated by “

0”

.

10. The method of claim 5, wherein the at least one personalized recommendation is displayed on the at least one screen in the form of at least one module, wherein the at least one module comprises at least one of:

at least one module for training personality changes, at least one module for personalized information, at least one module for personalized career guidance, at least one module for training personality changes, or combinations thereof.

11. The method of claim 3, wherein the at least one pscyhotype according to Briggs Myers is at least one of:

INTJ, INTP, ENTJ, ENTP, INFJ, INFP, ENFJ, ENFP, ISTJ, ISFJ, ESTJ, ESFJ, ISTP, ISFP, ESTP, or ESFP.

12. The method of claim 3, further comprising:

by the at least one processor, correlating the at least one pscyhotype according to Briggs Myers with the at least one personality trait according to the Big 5 to obtain at least one correlation; and

by the at least one processor, displaying the at least one correlation on the at least one screen of the at least one device.

13. The method of claim 3, wherein the at least one compatibility score is obtained by:

by the at least one processor, determining at least one personality metric of a first person;

by the at least one processor, determining at least one personality metric of a second person;

by the at least one processor, comparing the at least one personality metric of the first person with the at least one personality metric of the second person.

14. The method of claim 1, further comprising, by the at least one processor, validating the at least one PNN, as obtained during the inputting step, with at least a second set of annotated visual inputs.

15. The method of claim 14, wherein at least one of:

the set of annotated inputs or the second set of annotated visual inputs is annotated manually.

16. The method of claim 1, wherein the at least one set of visual inputs comprises at least one portrait image.

17. The method of claim 1, wherein each visual input of the set of visual inputs, the at least one additional visual input, or any combination thereof has an input resolution chosen from at least one of:

256×

256, 512×

512, 1024×

1024, 2048×

2048, 4096×

4096, 640×

480, 1280×

720, 800×

600, or combinations thereof.

18. The method of claim 1, wherein each visual input of the set of visual inputs, the at least one additional visual input, or any combination thereof has a color scheme chosen from at least one of:

RGB, YCrCb, YCbCr, YUV, LAB, or combinations thereof.

19. The method of claim 1, further comprising, by the at least one processor, normalizing each visual input of the set of visual inputs, normalizing the at least one additional visual input, or any combination thereof.

20. A system comprising:

a camera component, wherein the camera component is configured to acquire at least one visual input comprising a face of at least one person,

at least one processor;

a non-transitory computer memory, storing a computer program that, when executed by the at least one processor, causes the at least one processor to;

obtain at least one neural network,

obtain at least one set of visual inputs;

wherein each visual input of the at least one set of visual inputs comprises a face of at least one person;

annotate the at least one set of visual inputs with at least one set of results of at least one personality test, thereby obtaining at least one set of annotated visual inputs;

wherein each annotated visual input of the at least one set of annotated visual inputs comprises;

the face of the at least one person, and the result of the at least one personality test corresponding to the at least one person; and

input the at least one set of annotated visual inputs into the at least one neural network, so as to obtain at least one psychodiagnostic neural network (PNN);

obtain, at least one additional visual input comprising a face of at least one person;

input the at least one additional visual input into the at least one PNN, so as to obtain at least one personality metric of the at least one person of the at least one additional visual input;

wherein the at least one personality metric of the at least one person of the at least one additional visual input comprises;

at least one personality dimension of the at least one person of the at least one additional visual input, and

at least one numerical personality score, of the at least one person of the at least one additional visual input wherein the at least one numerical personality score provides a numerical indication of the strength of the at least one personality dimension; and

display at least one personality report on at least one screen of at least one computing device;

wherein the at least one personality report comprises the at least one personality metric of the at least one person of the at least one additional visual input.