View source for Meta platforms technologies, llc (20240119609). Distributed Sensing for Augmented Reality Headsets simplified abstract

=Distributed Sensing for Augmented Reality Headsets=


==Organization Name==

[[:Category:meta platforms technologies, llc|meta platforms technologies, llc]]


[[Category:meta platforms technologies, llc]]

==Inventor(s)==

[[:Category:Michael Goesele of Woodinville WA (US)|Michael Goesele of Woodinville WA (US)]][[Category:Michael Goesele of Woodinville WA (US)]]

[[:Category:Richard Andrew Newcombe of Seattle WA (US)|Richard Andrew Newcombe of Seattle WA (US)]][[Category:Richard Andrew Newcombe of Seattle WA (US)]]

[[:Category:Yujia Chen of Redmond WA (US)|Yujia Chen of Redmond WA (US)]][[Category:Yujia Chen of Redmond WA (US)]]

[[:Category:Florian Eddy Robert Ilg of Kirkland WA (US)|Florian Eddy Robert Ilg of Kirkland WA (US)]][[Category:Florian Eddy Robert Ilg of Kirkland WA (US)]]

[[:Category:Daniel Andersen of Redmond WA (US)|Daniel Andersen of Redmond WA (US)]][[Category:Daniel Andersen of Redmond WA (US)]]

[[:Category:Chao Li of Woodinville WA (US)|Chao Li of Woodinville WA (US)]][[Category:Chao Li of Woodinville WA (US)]]

[[:Category:Simon Gareth Green of Deptford (GB)|Simon Gareth Green of Deptford (GB)]][[Category:Simon Gareth Green of Deptford (GB)]]

==Distributed Sensing for Augmented Reality Headsets - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240119609 titled 'Distributed Sensing for Augmented Reality Headsets

==Simplified Explanation==

The abstract describes a distributed imaging system for augmented reality devices, where a computing module processes input images from spatially distributed sensing devices to generate output images through local feature matching and optical flow correspondence computations.

* The system includes a computing module in communication with multiple sensing devices.
* The computing module processes input images using local feature matching and optical flow correspondence computations.
* The output images are generated by combining the results of the local feature matching and optical flow correspondence computations.

== Potential Applications ==
This technology could be applied in various fields such as:
* Augmented reality applications
* Remote sensing
* Surveillance systems

== Problems Solved ==
This technology helps in:
* Improving the accuracy of augmented reality experiences
* Enhancing the performance of remote sensing devices
* Increasing the efficiency of surveillance systems

== Benefits ==
The benefits of this technology include:
* Enhanced image processing capabilities
* Improved image matching accuracy
* Real-time generation of output images

== Potential Commercial Applications ==
This technology could be commercially applied in:
* Augmented reality gaming
* Security and surveillance systems
* Remote sensing and monitoring

== Possible Prior Art ==
One possible prior art for this technology could be the use of distributed imaging systems in remote sensing applications.

=== Unanswered Questions ===

=== How does this technology impact the battery life of augmented reality devices? ===
This article does not address the potential impact of this technology on the battery life of augmented reality devices.

=== What are the limitations of the optical flow correspondence computation in this system? ===
The article does not discuss the potential limitations of the optical flow correspondence computation used in this system.


==Original Abstract Submitted==

a distributed imaging system for augmented reality devices is disclosed. the system includes a computing module in communication with a plurality of spatially distributed sensing devices. the computing module is configured to process input images from the sensing devices based on performing a local feature matching computation to generate corresponding first output images. the computing module is further configured to process the input images based on performing an optical flow correspondence computation to generate corresponding second output images. the computing module is further configured to computationally combine first and second output images to generate third output images.



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