DISNEY ENTERPRISES, INC. (20240242444). NEURAL EXTENSION OF 3D CONTENT IN AUGMENTED REALITY ENVIRONMENTS simplified abstract
Contents
NEURAL EXTENSION OF 3D CONTENT IN AUGMENTED REALITY ENVIRONMENTS
Organization Name
Inventor(s)
Hayko Jochen Wilhelm Riemenschneider of Zurich (CH)
Erika Varis Doggett of Los Angeles CA (US)
Evan Matthew Goldberg of Burbank CA (US)
Shinobu Hattori of Los Angeles CA (US)
Christopher Richard Schroers of Uster (CH)
NEURAL EXTENSION OF 3D CONTENT IN AUGMENTED REALITY ENVIRONMENTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240242444 titled 'NEURAL EXTENSION OF 3D CONTENT IN AUGMENTED REALITY ENVIRONMENTS
The abstract describes a technique for generating augmented reality (AR) content using machine learning models to create a 3D representation of physical space with anchor content.
- Input a layout of a physical space and anchor content into a machine learning model.
- Generate a 3D volume with a subset of the physical space and 3D representations of anchor content.
- Output views of the 3D volume on a computing device.
Potential Applications: - Augmented reality experiences in retail environments. - Virtual tours of real estate properties. - Interactive museum exhibits.
Problems Solved: - Enhancing user engagement with AR content. - Simplifying the creation process of AR experiences.
Benefits: - Improved user interaction with physical spaces. - Enhanced visualization of anchor content in real-world environments.
Commercial Applications: - Marketing campaigns with interactive AR elements. - Educational tools for immersive learning experiences.
Questions about AR Technology: 1. How does this technique improve the user experience of AR content? 2. What are the potential limitations of using machine learning models for generating AR content?
Frequently Updated Research: Stay updated on advancements in machine learning algorithms for AR content creation.
Original Abstract Submitted
one embodiment of the present invention sets forth a technique for generating augmented reality (ar) content. the technique includes inputting a first layout of a physical space and a first set of anchor content into a machine learning model. the technique also includes generating, via execution of the machine learning model, a first three-dimensional (3d) volume that includes (i) a first subset of the physical space and (ii) a placement of one or more 3d representations of the first set of anchor content in a second subset of the physical space. the technique further includes causing one or more views of the first 3d volume to be outputted in a computing device.
