View source for Intel corporation (20240192774). DETERMINATION OF GAZE POSITION ON MULTIPLE SCREENS USING A MONOCULAR CAMERA simplified abstract

=DETERMINATION OF GAZE POSITION ON MULTIPLE SCREENS USING A MONOCULAR CAMERA=


==Organization Name==

[[:Category:intel corporation|intel corporation]]


[[Category:intel corporation]]

==Inventor(s)==

[[:Category:Elad Sunray of Haifa (IL)|Elad Sunray of Haifa (IL)]][[Category:Elad Sunray of Haifa (IL)]]

[[:Category:Dmitry Rudoy of Haifa (IL)|Dmitry Rudoy of Haifa (IL)]][[Category:Dmitry Rudoy of Haifa (IL)]]

[[:Category:Noam Levy of Karmiel (IL)|Noam Levy of Karmiel (IL)]][[Category:Noam Levy of Karmiel (IL)]]

==DETERMINATION OF GAZE POSITION ON MULTIPLE SCREENS USING A MONOCULAR CAMERA - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240192774 titled 'DETERMINATION OF GAZE POSITION ON MULTIPLE SCREENS USING A MONOCULAR CAMERA

'''Simplified Explanation:'''
The patent application describes systems and methods for real-time, efficient, monocular gaze position determination using a neural network on a consumer-grade laptop. This technology can be used for various human-computer interactions, such as window selection, user attention tracking, gaming, augmented reality, and virtual reality.

'''Key Features and Innovation:'''
* Real-time, efficient gaze position determination using a monocular camera and neural network.
* Accuracy within about four degrees while maintaining low computational complexity.
* Ability to determine gaze position across multiple screens and identify user's viewing screen and gaze target area.
* Applicable to different head poses, facial expressions, cameras, screens, and illumination scenarios.

'''Potential Applications:'''
The technology can be used in various scenarios, including gaming, virtual reality, augmented reality, user interface design, attention tracking, and interactive displays.

'''Problems Solved:'''
This technology addresses the need for accurate and efficient gaze position determination in real-time using a consumer-grade laptop and a monocular camera.

'''Benefits:'''
* Enhanced user experience in human-computer interactions.
* Improved accuracy and efficiency in gaze tracking.
* Versatile applications in different scenarios and environments.

'''Commercial Applications:'''
The technology can be applied in industries such as gaming, virtual reality, augmented reality, user interface design, advertising, and market research to enhance user engagement and interaction.

'''Prior Art:'''
Prior research in gaze tracking technology, neural networks, and human-computer interaction can provide insights into the development and innovation of this technology.

'''Frequently Updated Research:'''
Stay updated on advancements in neural network technology, computer vision, and human-computer interaction research to enhance the performance and applications of this gaze position determination system.

'''Questions about Gaze Position Determination:'''
1. How does the neural network contribute to the accuracy and efficiency of gaze position determination?
2. What are the potential limitations of using a monocular camera for gaze tracking in different scenarios?


==Original Abstract Submitted==

systems and methods for real-time, efficient, monocular gaze position determination that can be performed in real-time on a consumer-grade laptop. gaze tracking can be used for human-computer interactions, such as window selection, user attention on screen information, gaming, augmented reality, and virtual reality. gaze position estimation from a monocular camera involves estimating the line-of-sight of a user and intersecting the line-of-sight with a two-dimensional (2d) screen. the system uses a neural network to determine gaze position within about four degrees of accuracy while maintaining very low computational complexity. the system can be used to determine gaze position across multiple screens, determining which screen a user is viewing as well as a gaze target area on the screen. there are many different scenarios in which a gaze position estimation system can be used, including different head poses, different facial expressions, different cameras, different screens, and various illumination scenarios.



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