Finding sequential matches in eye tracking data

• US 8,434,867 B2
• Filed: 11/10/2009
• Issued: 05/07/2013
• Est. Priority Date: 11/11/2008
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Helfman, Jonathan, Goldberg, Joseph H.
• Primary Examiner(s): Dinh, Jack
• Application Number:
  US12/615,736
• Publication Number:
  US 20100118267A1
• Time in Patent Office: 1,274 Days
• Field of Search: 351/209, 351/246, 351/206
• US Class Current: 351/209
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids

Abstract

Embodiments of the invention provide systems and methods for analyzing eye tracking data. The eye tracking data can represent a number of different scanpaths and can be analyzed, for example, to find patterns or commonality between the scanpaths. According to one embodiment, a method of analyzing eye tracking data can comprise receiving the eye tracking data which can include a plurality of scanpaths, each scanpath representing a sequence of regions of interest on a stimulus image. A dotplot can be generated and can include each of the plurality of scanpaths. One or more patterns within the eye tracking data can be identified based on the dotplot.

Claims

1. A method for analyzing eye tracking data, the method comprising:

receiving the eye tracking data at a path analysis system, wherein the eye tracking data comprises a plurality of scanpaths, each of the plurality of scanpaths representing a sequence of visual fixations on a stimulus image;

generating, with the path analysis system, a sequence of tokens corresponding to the sequence of visual fixations;

generating a dotplot, with the path analysis system, using the sequence of tokens; and

identifying, with the path analysis system, one or more patterns of sequentially matching tokens within the eye tracking data based on the dotplot.

2. The method of claim 1, wherein each token of the sequence of tokens corresponding to the sequence of visual fixations comprises a region name identifying one of a plurality of regions of interest of the stimulus image in which the corresponding visual fixation is located.

3. The method of claim 1, wherein identifying one or more patterns comprises identifying linear relationships within the plurality of scanpaths.

4. The method of claim 3, wherein identifying linear relationships within the plurality of scanpaths is based on a linear regression.

5. The method of claim 1, further comprising aggregating two or more scanpaths of the plurality of scanpaths with the path analysis system based on the identified one or more patterns.

6. The method of claim 5, further comprising displaying a representation of the aggregated two or more scanpaths with the path analysis system.

7. The method of claim 6, wherein the representation of the aggregated two or more scanpaths comprises a graphical representation of the stimulus image including an indication of the aggregated two or more scanpaths.

8. A system for analyzing eye tracking data, the system comprising:

a processor; and

a memory communicatively coupled with and readable by the processor and having stored therein a series of instructions which, when executed by the processor, cause the processor to receive the eye tracking data, wherein the eye tracking data comprises a plurality of scanpaths, each of the plurality of scanpaths representing a sequence of visual fixations on a stimulus image, generate a sequence of tokens corresponding to the sequence of visual fixations, generate a dotplot using the sequence of tokens, and identify one or more patterns of sequentially matching tokens within the eye tracking data based on the dotplot.

9. The system of claim 8, wherein each token of the sequence of tokens corresponding to the sequence of visual fixations comprises a region name identifying one of a plurality of regions of interest of the stimulus image in which the corresponding visual fixation is located.

10. The system of claim 8, wherein identifying one or more patterns comprises identifying linear relationships within the plurality of scanpaths.

11. The system of claim 10, wherein identifying linear relationships within the plurality of scanpaths is based on a linear regression.

12. The system of claim 8, wherein the instructions further cause the processor to aggregate two or more scanpaths of the plurality of scanpaths based on the identified one or more patterns.

13. The system of claim 12, wherein the instructions further cause the processor to display a representation of the aggregated two or more scanpaths.

14. The system of claim 13, wherein the representation of the aggregated two or more scanpaths comprises a graphical representation of the stimulus image including an indication of the aggregated two or more scanpaths.

15. A machine-readable memory device having stored thereon a sequence of instructions which, when executed by a processor, cause the processor to analyze eye tracking data by:

receiving the eye tracking data, wherein the eye tracking data comprises a plurality of scanpaths, each of the plurality of scanpaths representing a sequence of visual fixations on a stimulus image;

generating a sequence of tokens corresponding to the sequence of visual fixations;

generating a dotplot using the sequence of tokens; and

identifying one or more patterns of sequentially matching tokens within the eye tracking data based on the dotplot.

16. The machine-readable memory device of claim 15, wherein each token of the sequence of tokens corresponding to the sequence of visual fixations comprises a region name identifying one of a plurality of regions of interest of the stimulus image in which the corresponding visual fixation is located.

17. The machine-readable memory device of claim 15, wherein identifying one or more patterns comprises identifying linear relationships within the plurality of scanpaths.

18. The machine-readable memory device of claim 17, wherein identifying linear relationships within the plurality of scanpaths is based on a linear regression.

19. The machine-readable memory device of claim 15, further comprising aggregating two or more scanpaths of the plurality of scanpaths based on the identified one or more patterns.

20. The machine-readable memory device of claim 19, further comprising displaying a representation of the aggregated two or more scanpaths.

21. The machine-readable memory device of claim 20, wherein the representation of the aggregated two or more scanpaths comprises a graphical representation of the stimulus image including an indication of the aggregated two or more scanpaths.