Robot for preventing interruption while interacting with user
US-12169410-B2 · Dec 17, 2024 · US
US9442565B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9442565-B2 |
| Application number | US-201213592500-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 23, 2012 |
| Priority date | Aug 24, 2011 |
| Publication date | Sep 13, 2016 |
| Grant date | Sep 13, 2016 |
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System and method for analyzing multiple participants' eye-movements over a visual display to determine which features on the display universally attract the most attention, or are the most distracting.
Opening claim text (preview).
What is claimed is: 1. A computer method for analyzing multiple observers' fixations, recorded by an eye-tracker, over a visual display to determine distracting features, comprising the steps of: using the eye-tracker to detect fixations of a plurality of observers on an electronic display, each of the fixations being associated with an observer of the plurality of observers; snapping each of the fixations to a nearest grid location of a grid based on a preset resolution; clustering together the snapped fixations of the plurality of observers within a pre-selected visual angle of other of the snapped fixations in the electronic display; isolating the clustered fixations associated with at least a pre-selected percentage of the plurality of observers; removing the fixations that are not part of the isolated clustered fixations; expanding the isolated clustered fixations to represent a pre-selected output visual angle; and updating the electronic display to highlight the expanded isolated clustered fixations as the distracting features. 2. The method as in claim 1 wherein the pre-selected visual angle comprises a user-selected visual angle. 3. The method as in claim 1 wherein the pre-selected output visual angle comprises a user-selected output visual angle. 4. The method as in claim 1 wherein the step of detecting fixations comprises the step of: configuring an electronic automated device for detecting the fixations. 5. The method as in claim 1 further comprising the step of: excluding predetermined fixations. 6. The method as in claim 5 wherein the predetermined fixations comprise the first fixation in each trial, the fixations following the successful completion of some task, the fixations affected by drift of the eye tracking device, and the fixations over specified features. 7. The method as in claim 5 wherein the step of automatically expanding comprises the step of: adding a border of pre-selected pixel width to the isolated clustered fixations. 8. The method as in claim 7 wherein the pre-selected pixel width comprises a user-selected pixel width. 9. The method as in claim 1 further comprising the step of: while forming each cluster, automatically calculating and maintaining a running summation and count of parameters associated with each fixation in each cluster. 10. The method as in claim 9 wherein the parameters comprise a number of unique observers represented by the fixations in each cluster, the duration of each of the fixations in each cluster, the index of each fixation in each cluster, and other measureable, user-specified parameters associated with each fixation in each cluster. 11. The method as in claim 9 further comprising the step of: after forming each cluster, automatically calculating the number of unique observers represented by the fixations in each cluster; automatically calculating statistical measures for each of the parameters calculated for the fixations in each cluster; and automatically providing the clustered fixation statistics for each of the distracting features. 12. A computer system for analyzing multiple observers' fixations, recorded by a tracking device, over a visual display to determine distracting features comprising: a detector detecting, from tracking device data from the tracking device, the fixations on the visual display, each of the fixations being associated with one of a plurality of observers; a cluster processor: snapping each of the fixations to a nearest grid location of a grid based on a preset resolution, and clustering together the snapped fixations within a pre-selected visual angle of other of the snapped fixations; an isolator isolating the clustered fixations associated with at least a pre-selected percentage of the plurality of observers; a remover removing the fixations that are not part of the processed clustered fixations; an expander expanding the isolated clustered fixations to represent a pre-selected output visual angle, the expander providing to a chart processor expanded isolated clustered fixations; and the chart processor updating the visual display to highlight the expanded isolated clustered fixations as the distracting features. 13. The system as in claim 12 wherein the detector comprises computer code on a computer readable medium for: providing configuration information to the tracking device for detecting the fixations. 14. The system as in claim 12 wherein the excluder comprises computer code on a computer readable medium for: excluding predetermined of the fixations, where the predetermined of the fixations comprise the first of the fixations in each trial, the fixations following the successful completion of a task, the fixations affected by drift of the tracking device, and the fixations over specified features. 15. The system as in claim 12 wherein the expander comprises computer code on a computer readable medium for creating a border of pre-selected pixel width to isolate the clustered fixations. 16. The system as in claim 12 wherein the cluster processor comprises: a cluster statistics processor automatically calculating and maintaining parameter statistics associated with each of the fixations in each of the clustered fixations. 17. The system as in claim 16 wherein the parameter statistics comprise: the number of unique observers represented by the fixations in each of the clustered fixations; the duration of each of the fixations in each of the clustered fixations; the index of each of the fixations in each of the clustered fixations; and other user-specified parameters associated with each of the fixations in each of the clustered fixations. 18. The system as in claim 16 wherein the cluster statistics processor comprises computer code stored on a computer readable medium for: after forming each of the clustered fixations, automatically calculating a number of unique observers represented by the fixations in each of the clustered fixations; and automatically calculating statistical measures for each of the parameters calculated for the fixations in each of the clustered fixations. 19. The system as in claim 12 wherein the cluster processor comprises: distractions statistics processor automatically providing clustered fixation statistics for each of the distracting features.
Zoom, i.e. interaction techniques or interactors for controlling the zooming operation · CPC title
Vertical resolution change · CPC title
Scaling of whole images or parts thereof, e.g. expanding or contracting · CPC title
Resolution change, inclusive of the use of different resolutions for different screen areas · CPC title
based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance · CPC title
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