Method for presenting high level interpretations of eye tracking data correlated to saved display images

• US 6,106,119 A
• Filed: 11/09/1999
• Issued: 08/22/2000
• Est. Priority Date: 10/16/1998
• Status: Expired

• Current Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford University)
• Original Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford University)
• Inventors: Edwards, Gregory T.
• Primary Examiner(s): MANUEL, GEORGE C
• Application Number:
  US09/437,735
• Time in Patent Office: 287 Days
• Field of Search: 351/200, 351/203, 351/209, 351/246, 600/544, 600/545, 359/630, 345/156, 345/157, 345/158, 345/8
• US Class Current: 351/209
• CPC Class Codes: A61B 3/0025 characterised by electronic signal processing, e.g. eye models
• CPC Class Codes: A61B 3/0058 for multiple images
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence

Abstract

A software program stores during a recording session eye-tracking data and all other communication device activities of a test person that self-controlled confronts her/himself with display scenarios or virtual pages. The display scenarios are stored simultaneously either:

1. after a predetermined elapse time interval,

2. after recognizing a raised attention level of the test person,

3. after a positive result of a scrolling detection process.

In a consecutive processing cycle, the software program utilizes an eye interpretation engine to derive high level informations and visualizes them superimposed on the correlated image scenarios.

Claims

1. A method for presenting high level interpretations of eye tracking data correlated to stored display scenarios of a display event, said method comprising following steps:

A) storing eye tracking data and correlated display scenarios, said display scenarios being stored according to at least one of the following conditions;

1) a predetermined elapsed time interval;

2) a predetermined tracking sequence of said eye tracking data, said eye tracking data being derived and simultaneously evaluated;

3) a positive result of a scrolling detection process; and

4) a predetermined communication device activity;

B) processing said eye tracking data with an interpretation engine, whereby said eye tracking data is converted into said high level interpretations;

C) assigning a valuation vocabulary to said high level interpretations; and

D) displaying said stored display scenarios and presenting simultaneously said valuation vocabulary.

2. The method of claim 1, whereby said stored display scenarios are segments of a virtual page.

3. The method of claim 2, whereby said virtual page exceeds a viewable display area.

4. The method of claim 1, whereby said display scenario compromises a scrollable area.

5. The method of claim 4, whereby said virtual page is partially and scrollable displayed within said scroll area.

6. The method of claim 4, whereby a coordinate information is stored simultaneously and correlated to said eye-tracking data.

7. The method of claim 6, whereby said coordinate information is referenced to a viewable display area.

8. The method of claim 6, whereby said coordinate information is referenced to said virtual page.

9. The method of claim 6, whereby said coordinate information is referenced to said scrollable area.

10. The method of claim 1, whereby said predetermined tracking sequence corresponds to a predetermined attention level increase.

11. The method of claim 1, whereby said predetermined tracking sequence indicates a condition change of said display event.

12. The method of claim 1, whereby said scrolling detection process is a detection algorithm consisting of the following three steps:

A) continuously collecting data from an operation system about windows appearing during display events;

B) analyzing said windows to recognize scrolling windows; and

C) detecting location alterations of said scrolling windows.

13. The method of claim 1, whereby said scrolling detection analysis in real time a pixel matrix for pixel patterns.

14. The method of claim 13, whereby said pixel matrix is a display scenario.

15. The method of claim 13, whereby said pixel pattern relates to a scrolling initiation function.

16. The method of claim 1, whereby said high level interpretations correspond to eye behavior patterns.

17. The method of claim 1, whereby said high level interpretations correspond to basic mental states.

18. The method of claim 1, whereby said valuation vocabulary is an acoustic vocabulary.

19. The method of claim 1, whereby said valuation vocabulary is a graphical vocabulary.

20. The method of claim 19, whereby said graphical vocabulary is superimposed displayed with said stored display scenario.

21. The method of claim 19, whereby said graphical vocabulary is selectable displayed.

22. The method of claim 1, whereby said valuation vocabulary corresponds to demographic information retrieved by applying said method in a number of corresponding testing sessions.

23. The method of claim 1, whereby said valuation vocabulary corresponds to statistic information retrieved by applying said method in a number of corresponding testing sessions.

24. The method of claim 1, whereby said method is executed in form of a machine-readable code and stored on a storing device.

25. The method of claim 24, whereby said machine-readable code is part of a web browser.

26. The method of claim 24, whereby said machine-readable code is a self extracting attachment of a web page.