NEURAL EXTENSION OF 3D CONTENT IN AUGMENTED REALITY ENVIRONMENTS

Number: 20240242444
Published: 2024-07-18
Filed: 2023-01-17
Assignee: DISNEY ENTERPRISES, INC.
Inventors: Riemenschneider; Hayko Jochen Wilhelm et al.
CPC: G06V10/26; G06T15/08; G06T19/006; G06V10/82; G06T19/20
Verdict: Low Notable software
Source: Google Patents · FreePatentsOnline

The keeper's note

Neural extension technique for 3D content in AR environments.

Abstract

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.

Background

BACKGROUND Field of the Various Embodiments

Embodiments of the present disclosure relate generally to machine learning and augmented reality and, more specifically, to neural extension of three-dimensional (3D) content in augmented reality environments. Description of the Related Art

Augmented reality (AR) refers to the merging of real-world and computer-generated content into an interactive sensory experience. For example, an AR system could include a camera, depth sensor, microphone, accelerometer, gyroscope, and/or another type of sensor that detects events or changes in the environment around a user. The AR system could also include a display, speaker, and/or another type of output device that combines data collected by the sensors with additional AR content into an immersive experience. The AR system could additionally modify the output of real-world and/or AR content in response to changes in the environment, interaction between the user and the AR content, and/or other input.

One application of AR involves combining traditional media content, such as images, audio, and/or video, with the layout of a real-world physical space. For example, an AR system executing on a wearable device or portable electronic device could “extend” an image or video of a scene across a room by overlaying objects, shapes, colors, and/or textures from the scene onto walls, ceilings, floors, and/or other parts of the room. The AR system could also arrange various portions o

Claims

1. A computer-implemented method for generating augmented reality content, the method comprising: inputting a first layout of a physical space and a first set of anchor content into a machine learning model; 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; and causing one or more views of the first 3D volume to be outputted in a computing device. || 11. One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of: inputting a first layout of a physical space and a first set of anchor content into a machine learning model; 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; and causing one or more views of the first 3D volume to be outputted in a computing device. || 20. A system, comprising: one or more memories that store instructions, and one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to perform the steps of: inputting a first representation of a physical space and a first set of anchor content into a machine learning model; 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; and causing one or more views of the first 3D volume to be outputted in a computing device.