Generation of test stimuli in visual media

• US 20070105071A1
• Filed: 11/06/2006
• Published: 05/10/2007
• Est. Priority Date: 11/04/2005
• Status: Active Grant

• Current Assignee: EyeTracking, Inc.
• Original Assignee: EyeTracking, Inc.
• Inventors: Weatherhead, James
• Granted Patent: US 8,602,791 B2
• Time in Patent Office: Days
• US Class Current: 434/81
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/16 Devices for psychotechnics using teaching or educational appliances G09B1/00 - G09B7/00; Testing reaction times ; Devices for evaluating the psychological state
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Test stimuli for visual media may be generated by incorporation of one or more element images selected from a library into a presentation area. The test stimuli may be displayed or presented to one or more subjects and metrics indicating the attentiveness of the subjects to various locations in the composite image may be measured. These metrics may be analyzed with placement parameters for incorporation of the element images into the composite image to determine subject reactions to various aspects of the test stimuli.

Claims

1. A computer-implemented method comprising:

generating a composite image that includes an element image that is selected from a library;

tracking one or more placement parameters related to inclusion of the element image in the composite image;

presenting the composite image to a subject;

recording a metric indicative of subject attentiveness to one or more locations in the composite image; and

correlating the recorded metric with the one or more placement parameters to characterize a level of subject interest in the element image.

2. A computer-implemented method as in claim 1, further comprising stochastically generating the placement parameters.

3. A computer-implemented method as in claim 1, further comprising stochastically selecting the element image from all of the element images in the library.

4. A computer-implemented method as in claim 1, wherein the element image is selected automatically and stochastically from a user-defined subset of element images in the library.

5. A computer-implemented method as in claim 1, further comprising defining the library with one or more selected element images.

6. A computer-implemented method as in claim 1, wherein the library is a set of element images selected from a larger collection of images.

7. A computer-implemented method as in claim 1, further comprising defining a plurality of regions within the composite image such that the element image may be placed into one of the plurality of regions.

8. A computer-implemented method as in claim 1, wherein the placement parameters are one or more of a location within the composite image, an absolute dimension of the element image, a relative dimension of the element image, an orientation of the element image, a metric of a degree to which the element image is occluded by one or more features of the composite image, and a metric of transparency of the element image or a part thereof.

9. A computer-implemented method as in claim 1, wherein the metric of subject attentiveness comprises one or more of eye tracking data, input from a user input device, and input from one or more psycho-physiological measuring devices.

10. A computer-implemented method as in claim 1, further comprising:

selecting an additional element image from the library; and

including the additional element image in the composite image.

11. A computer-implemented method comprising:

scaling a first element image selected from a library relative to a content of a presentation area;

incorporating the first element image into the presentation area at a defined location to form a composite image;

recording information related to the incorporation of the element image into the composite image;

presenting the composite image to one or more test subjects;

recording external data related to the test subject viewing of the composite image; and

analyzing the external data in correlation with the information related to incorporation of the element image in the composite image to characterize a level of subject interest in the element image.

12. A computer-implemented method as in claim 11, wherein the defined location is determined stochastically.

13. A computer-implemented method as in claim 11, wherein the information related to incorporation of the element image in the composite image is one or more of a location of the element image within the composite image, a dimension of the element image within the composite image, an orientation of the element image within the composite image, and a staging of the element image within the composite image.

14. A computer-implemented method as in claim 11, wherein the external data are eye tracking data or input from a user input device related to one or more locations within the composite image.

15. A computer-implemented method as in claim 11, wherein the analysis comprises correlating a frequency with which the external data intersect an area occupied by the element image in the composite image.

16. A computer-implemented method as in claim 11, wherein the analysis comprises correlating a frequency with which the external data transfer into or out of an area occupied by the element image in the composite image.

17. A computer-implemented method as in claim 11, wherein the analysis comprises correlating a sequence in which the external data transition between an area occupied by the element image in the composite image and another area within the composite image.

18. A computer-implemented method as in claim 11, further comprising recording second external data at a time corresponding to an instance in which the external data intersect an area occupied by the element image in the composite image.

19. A computer-implemented method as in claim 18, wherein the second external data are produced from one or more sources selected from computer input devices and psycho-physiological measuring devices.

20. A computer-implemented method as in claim 11, further comprising recording second external data at a time corresponding to an instance in which the external data transfer into or out of an area occupied by the element image in the composite image.

21. A computer-implemented method as in claim 20, wherein the second external data are produced from one or more sources selected from computer input devices and psycho-physiological measuring devices.

22. A computer-implemented method as in claim 11, further comprising recording second external data at a time corresponding to an instance in which the external data transition between an area occupied by the element image in the composite image and another area within the composite image.

23. A computer-implemented method as in claim 22, wherein the second external data are produced from one or more sources selected from computer input devices and psycho-physiological measuring devices.

24. A computer-implemented method comprising:

presenting a plurality of composite images to a plurality of subjects, each composite image being generated by incorporating one or more of a plurality of element images selected from a library into a presentation area according to one or more placement parameters;

recording a metric indicative of attentiveness of each of the plurality of subjects to one or more locations in the plurality of composite images; and

correlating the recorded metric with the one or more placement parameters to characterize a level of subject interest in the element image.

25. A computer-implemented method as in claim 24, wherein the one or more element images incorporated into each composite image in the plurality of composite images is selected stochastically from the library.

26. A computer-implemented method as in claim 24, further comprising stochastically generating the one or more placement parameters for each of the one or more element images in each of the plurality of composite image.

27. A computer-implemented method as in claim 24, further comprising stochastically generating a different ordering in which the plurality of composite images is shown to one or more of the plurality of subjects.

28. A computer-implemented method as in claim 24, further comprising aggregating the metric indicative of subject attentiveness into a data set and analyzing the aggregated data set by one or more statistical measures.