PRESENTATION OF MATERIALS BASED ON LOW LEVEL FEATURE ANALYSIS

• US 20140365310A1
• Filed: 06/05/2013
• Published: 12/11/2014
• Est. Priority Date: 06/05/2013
• Status: Abandoned Application

• Current Assignee: Apple Inc.
• Original Assignee: Machine Perception Technologies Inc. (Apple Inc.)
• Inventors: MOVELLAN, Javier
• Application Number:
  US13/911,037
• Publication Number:
  US 20140365310A1
• Time in Patent Office: Days
• US Class Current: 705/14.66
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06V 10/446 using Haar-like filters, e.g. using integral image techniques
• CPC Class Codes: G06V 40/168 Feature extraction; Face representation

Abstract

A computer system obtains an image or video of a person, such as a shopper. The image or video includes the face of the person. The system extracts low level features from the image or video. The low level features may be Gabor features. The system examines the low level features to designate stimuli that are likely to result in preferred behaviors associated with the person. The system analyzes the plurality of designated stimuli based on predetermined criteria to select one or more selected stimuli, and then causes the selected stimuli to be rendered to the person. The predetermined criteria may be economic criteria, such as a requirement to select the stimulus with the highest expected economic benefit from among the various designated stimuli.

Claims

1. A computer-implemented method comprising steps of:

obtaining at least one image of a person, the at least one image comprising at least part of a face of the person;

extracting low level features from the at least one image, thereby obtaining extracted low level features;

examining the extracted low level features to designate one or more designated stimuli likely to result in one or more preferred behaviors associated with the person; and

rendering at least one stimulus from among the one or more designated stimuli.

2. A computer-implemented method according to claim 1,

wherein the one or more designated stimuli comprise a plurality of designated stimuli;

the method further comprises analyzing the plurality of designated stimuli based on one or more predetermined criteria to select the at least one selected stimulus; and

the step of rendering comprises rendering the at least one selected stimulus.

3. A computer-implemented method according to claim 2, wherein the step of extracting comprises applying a plurality of Gabor filters to an output of a pixel mask of the at least one image.

4. A computer-implemented method according to claim 2, wherein the step of extracting comprises applying a plurality of Box Filters to an output of a pixel mask of the at least one image.

5. A computer-implemented method according to claim 2, wherein the step of extracting comprises applying a sequence of Haar Wavelets to the at least one image.

6. A computer-implemented method according to claim 2, wherein the step of extracting comprises applying a scale-invariant feature transform to the at least one image.

7. A computer-implemented method according to claim 2, wherein the step of extracting comprises at least one of:

applying a plurality of filters to an output of a pixel mask of the at least one image;

applying a sequence of Haar Wavelets to the at least one image; and

applying a scale-invariant feature transform to the at least one image.

8. A computer-implemented method according to claim 7, wherein the step of examining comprises comparing the extracted low level features to reference features in one or more databases with associations of the reference features and behaviors, so that the one or more designated stimuli are likely to result in one or more preferred behaviors.

9. A computer-implemented method according to claim 8, wherein the step of analyzing comprises evaluating the plurality of designated stimuli based on one or more economic criteria to select a single stimulus with highest expected economic return from among the plurality of designated stimuli.

10. A computer-implemented method according to claim 8, wherein the step of analyzing comprises evaluating the plurality of designated stimuli based on one or more economic criteria to select at least two stimuli so that expected economic return is highest possible for any subset of two or more stimuli from among all the designated stimuli.

11. A computer-implemented method according to claim 8, wherein the step of analyzing comprises evaluating the plurality of designated stimuli based on one or more economic criteria to select the at least one selected stimulus.

12. A computer-implemented method according to claim 11, wherein the at least one selected stimulus comprises an image.

13. A computer-implemented method according to claim 11, wherein the at least one selected stimulus comprises a sound.

14. A computer-implemented method according to claim 11, wherein the at least one selected stimulus comprises a smell.

15. A computer-implemented method according to claim 11, wherein the at least one selected stimulus comprises presentation of a product.

16. A computer-implemented method according to claim 11, further comprising storing a reaction of the person to the at least one selected stimulus.

17. A computer-implemented method according to claim 11, further comprising storing an outcome caused by the at least one selected stimulus.

18. A computer-implemented method according to claim 18, wherein the outcome comprises data describing occurrence or non-occurrence of a transaction with the person or with another person associated with the person.

19. A computer based system comprising a processor, a memory storing machine readable instructions, a display, and a camera, the system being configured to

obtain through the camera at least one image of a person, the at least one image comprising at least part of a face of the person;

extract low level features from the at least one image, thereby obtaining extracted low level features;

examine the extracted low level features to designate one or more designated stimuli likely to result in one or more preferred behaviors associated with the person; and

render on the display at least one stimulus from among the one or more designated stimuli.

20. A computer based system according to claim 19, wherein

the one or more designated stimuli comprise a plurality of designated stimuli;

and

the system is further configured to analyze the plurality of designated stimuli based on one or more predetermined criteria to select the at least one stimulus from among the plurality of designated stimuli.

21. An article of manufacture comprising one or more memory devices storing computer code, wherein the code, when executed by at least one computer based system, configures the at least one computer based system to perform a method comprising:

obtaining at least one image of a person, the at least one image comprising at least part of a face of the person;

extracting low level features from the at least one image, thereby obtaining extracted low level features;

examining the extracted low level features to designate one or more designated stimuli likely to result in one or more preferred behaviors associated with the person; and

rendering at least one stimulus from among the one or more designated stimuli.

22. An article of manufacture according to claim 21, wherein:

the one or more designated stimuli of the method comprise a plurality of designated stimuli;

the method further comprises analyzing the plurality of designated stimuli based on one or more predetermined criteria to select the at least one selected stimulus; and

the step of rendering comprises rendering the at least one selected stimulus.