Creating Your Own Image in Virtual and Augmented Reality
This patent describes how an artificial reality system can show a user their own image, called a self-representation, within a virtual world by using machine learning to identify and display parts of their live image.
Original patent title: “Providing a secured self-representation by writing to a portion if a frame buffer after other applications have written to the frame buffer, where the other applications cannot access the secured-self representation or the images received by a secure application”
This patent describes how an artificial reality system can show a user their own image, called a self-representation, within a virtual world by using machine learning to identify and display parts of their live image. Granted in 2026.
Coverage
What does this patent actually cover?
Based on the abstractabstractA short summary at the front of the patent describing the invention. Not legally binding.Read more →, this patent describes a system that creates a digital version of a user, called a self-representation, for artificial reality environments. It works by taking an image of the user and then using a special computer program, a machine learning model, to find the 'self portion' of that image. This model has been taught to recognize parts of images that show a user from their own perspective. Once identified, this self-representation is placed into the artificial reality world, adjusted to match the user's viewpoint. The system also tracks the user's movements and updates their digital self-representation to move along with them, making it more realistic. For example, if a user is in a virtual meeting, this system could display a live, moving image of their face as their avatar.
The gap
What does this patent NOT cover?
- Does not cover creating a self-representation purely from a 3D model generated without an initial image of the user.
- Does not cover self-representations that are not based on classifying a 'self portion' from an image using a machine learning model.
- Does not cover systems where the self-representation is static and does not adjust to the user's real-time movements.
- Does not cover displaying generic avatars or pre-made character models that do not originate from the user's live image.
- Does not cover methods of self-representation that do not involve positioning the representation relative to the user's perspective in the artificial reality environment.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The clever part is using a machine learning model specifically trained to classify a 'self portion' from an image based on a 'self-perspective'. This allows the system to intelligently extract and display the relevant part of the user's image, rather than simply showing a raw video feed, and then dynamically adjust it within the artificial reality environment.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Meta Quest avatars with camera passthrough
Microsoft Mesh for collaborative virtual spaces
Apple Vision Pro persona generation
Zoom or Google Meet virtual backgrounds that integrate the user's image
Any future augmented or virtual reality system requiring realistic user avatars
Why it matters
The bigger picture
Accurate and dynamic self-representations are crucial for making artificial reality experiences feel real and immersive. This technology could enhance social interactions in virtual spaces, allowing users to see a more authentic version of themselves. It improves the sense of presence and connection in applications ranging from virtual meetings to collaborative design environments. The ability to dynamically update the representation with user movement makes interactions more natural.
Filed
October 30, 2023
Granted
September 15, 2026
Market context
Who's building on this
Companies in this space
Major technology companies like Meta, Apple, and Microsoft are actively developing and integrating similar capabilities into their artificial reality platforms. Startups focused on virtual collaboration and social VR experiences are also building on the concept of realistic and dynamic user representation. These companies are continually refining how users appear and interact within virtual and augmented spaces.
Market impact
This technology contributes to the ongoing development of more immersive and personalized artificial reality experiences. It enables more natural social interactions in virtual environments, potentially increasing user engagement and adoption of AR/VR platforms. By providing a more authentic self-representation, it could reduce the 'uncanny valley' effect often associated with digital avatars, making virtual interactions feel more human and less artificial, thereby expanding the market for professional and social AR/VR applications.
Claim 1 — Plain English
What this patent covers
Based on the abstract, this patent describes a system that creates a digital version of a user, called a self-representation, for artificial reality environments. It works by taking an image of the user and then using a special computer program, a machine learning model, to find the 'self portion' of that image. This model has been taught to recognize parts of images that show a user from their own perspective. Once identified, this self-representation is placed into the artificial reality world, adjusted to match the user's viewpoint. The system also tracks the user's movements and updates their digital self-representation to move along with them, making it more realistic. For example, if a user is in a virtual meeting, this system could display a live, moving image of their face as their avatar.
The clever bit
The clever part is using a machine learning model specifically trained to classify a 'self portion' from an image based on a 'self-perspective'. This allows the system to intelligently extract and display the relevant part of the user's image, rather than simply showing a raw video feed, and then dynamically adjust it within the artificial reality environment.
What it does not cover
- Does not cover creating a self-representation purely from a 3D model generated without an initial image of the user.
- Does not cover self-representations that are not based on classifying a 'self portion' from an image using a machine learning model.
- Does not cover systems where the self-representation is static and does not adjust to the user's real-time movements.
- Does not cover displaying generic avatars or pre-made character models that do not originate from the user's live image.
- Does not cover methods of self-representation that do not involve positioning the representation relative to the user's perspective in the artificial reality environment.
Patent timeline
Application submitted to the patent office
Patent officially issued
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
0/20
Narrow claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$19K – $61K
Midpoint $38K · 17.1 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
Concepts involved
Cite this patent
(2026). Creating Your Own Image in Virtual and Augmented Reality (U.S. Patent No. 12,737,996). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12737996/providing-a-secured-self-representation-by-writing-to-a-portion-if-a-frame
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does Creating Your Own Image in Virtual and Augmented Reality cover?
This patent describes how an artificial reality system can show a user their own image, called a self-representation, within a virtual world by using machine learning to identify and display parts of their live image.
When does this patent expire?
This patent is expected to expire on September 15, 2046, when the invention enters the public domain.
What problem does this patent solve?
Accurate and dynamic self-representations are crucial for making artificial reality experiences feel real and immersive. This technology could enhance social interactions in virtual spaces, allowing users to see a more authentic version of themselves. It improves the sense of presence and connection in applications ranging from virtual meetings to collaborative design environments. The ability to dynamically update the representation with user movement makes interactions more natural.
What does this patent NOT cover?
Does not cover creating a self-representation purely from a 3D model generated without an initial image of the user.
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