Implicit Calibration from Screen Content for Gaze Tracking

Organization Name

Inventor(s)

Pezhman Firoozfam of Mountain View CA (US)

Implicit Calibration from Screen Content for Gaze Tracking - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240126365 titled 'Implicit Calibration from Screen Content for Gaze Tracking

Simplified Explanation

The technology described in the patent application is for implicit calibration for gaze tracking using a neural network module. The neural network module receives display content associated with a display screen, uncalibrated gaze information, and applies a selected function to generate a user-specific gaze function. This user-specific gaze function is then applied to the uncalibrated gaze information to generate calibrated gaze information associated with the display content.

Implicit calibration for gaze tracking using a neural network module
Receiving display content and uncalibrated gaze information
Applying a selected function to generate a user-specific gaze function
Applying the user-specific gaze function to the uncalibrated gaze information to generate calibrated gaze information

Potential Applications

This technology can be applied in various fields such as:

Virtual reality systems
Eye-tracking devices for accessibility purposes
Market research for analyzing consumer behavior

Problems Solved

The technology addresses the following issues:

Improving accuracy in gaze tracking
Personalizing gaze calibration for individual users
Enhancing user experience in interactive systems

Benefits

The benefits of this technology include:

Enhanced user experience in virtual environments
Improved accessibility for individuals with disabilities
More accurate data collection for research and analysis purposes

Potential Commercial Applications

This technology has potential commercial applications in:

Gaming industry for immersive experiences
Healthcare sector for assistive technologies
Advertising and marketing for targeted campaigns

Possible Prior Art

One possible prior art for this technology could be existing gaze tracking systems that use explicit calibration methods rather than implicit calibration through neural networks.

Unanswered Questions

How does this technology compare to traditional gaze tracking methods?

This article does not provide a direct comparison between this technology and traditional gaze tracking methods.

What are the limitations of using a neural network module for implicit gaze calibration?

The article does not address any potential limitations or challenges associated with using a neural network module for implicit gaze calibration.

Original Abstract Submitted

the technology relates to methods and systems for implicit calibration for gaze tracking. this can include receiving, by a neural network module, display content that is associated with presentation on a display screen (). the neural network module may also receive uncalibrated gaze information, in which the uncalibrated gaze information includes an uncalibrated gaze trajectory that is associated with a viewer gaze of the display content on the display screen (). a selected function is applied by the neural network module to the uncalibrated gaze information and the display content to generate a user-specific gaze function (). the user-specific gaze function has one or more personalized parameters. and the neural network module can then apply the user-specific gaze function to the uncalibrated gaze information to generate calibrated gaze information associated with the display content on the display screen (). training and testing information may alternatively be created for implicit gaze calibration ().

Google llc (20240126365). Implicit Calibration from Screen Content for Gaze Tracking simplified abstract

Contents

Implicit Calibration from Screen Content for Gaze Tracking

Organization Name

Inventor(s)