Generating three-dimensional content from two-dimensional images
US-11113887-B2 · Sep 7, 2021 · US
US12330039B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12330039-B2 |
| Application number | US-202418817694-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 28, 2024 |
| Priority date | Aug 30, 2023 |
| Publication date | Jun 17, 2025 |
| Grant date | Jun 17, 2025 |
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One example relates to a method for providing an immersive virtual golf service using an eXtended Reality (XR). The method may comprise: capturing an image of an actual golf ball placed on a ground through a camera of an XR device; reproducing and displaying the image within a virtual golf environment displayed on a display unit of the XR device; capturing, in real-time, a golf swing of a user through the camera of the XR device; analyzing a golf swing motion of the user in real-time using an artificial neural network model; and reproducing and displaying the analyzed golf swing motion within the virtual golf environment displayed on the display unit of the XR device.
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What is claimed is: 1. A method for providing an immersive virtual golf service using an eXtended Reality (XR), the method comprising: capturing an image of an actual golf ball placed on a ground through a first plurality of cameras which are arranged to face forward of the XR device and a second plurality of cameras which are arranged to face downward of the XR device; reproducing and displaying the image within a virtual golf environment displayed on a display unit of the XR device; capturing, in real-time, a golf swing of a user through the first plurality of cameras and the second plurality of cameras; analyzing a golf swing motion of the user in real-time using an artificial neural network model; and reproducing and displaying the analyzed golf swing motion within the virtual golf environment displayed on the display unit of the XR device. 2. The method of claim 1 , wherein the artificial neural network model is stored in the XR device. 3. The method of claim 1 , wherein the artificial neural network model includes: a first artificial neural network model configured for object detection, object segmentation, or object tracking. 4. The method of claim 1 , wherein the artificial neural network model includes: a second artificial neural network model configured for a pose estimation. 5. The method of claim 1 , wherein the artificial neural network model includes: a third artificial neural network model configured for scaling. 6. The method of claim 1 , wherein the artificial neural network model includes: a fourth artificial neural network model configured for motion prediction. 7. The method of claim 1 , wherein the XR device includes a neural processing unit configured to perform computations for the artificial neural network model. 8. The method of claim 1 , further comprising: displaying a virtual golfer's swing in caparison with a user's golf swing. 9. The method of claim 1 , further comprising: scaling a body of a virtual golfer displayed on the XR device based on body dimensions of the user. 10. An eXtended Reality (XR) device comprising: a first plurality of cameras which are arranged to face forward; a second plurality of cameras which are arranged to face downward; a display unit; and a controller configured to control the camera and display and perform steps of: capturing an image of an actual golf ball placed on a ground through the first plurality of cameras and the second plurality of cameras, reproducing and displaying the image within a virtual golf environment displayed on the display unit, capturing, in real-time, a golf swing of a user through the first plurality of cameras and the second plurality of cameras, analyzing a golf swing motion of the user in real-time using an artificial neural network model, and reproducing and displaying the analyzed golf swing motion within the virtual golf environment displayed on the display unit. 11. The XR device of claim 10 , wherein the artificial neural network model is stored in the XR device. 12. The XR device of claim 10 , wherein the artificial neural network model includes: a first artificial neural network model configured for object detection, object segmentation, or object tracking. 13. The XR device of claim 10 , wherein the artificial neural network model includes: a second artificial neural network model configured for a pose estimation. 14. The XR device of claim 10 wherein the artificial neural network model includes: a third artificial neural network model configured for scaling. 15. The XR device of claim 10 , wherein the artificial neural network model includes: a fourth artificial neural network model configured for motion prediction. 16. A non-volatile computer-readable storage medium storing instructions, the instructions, when executed by one or more processors, causing the one or more processors to perform steps comprising: capturing an image of an actual golf ball placed on a ground through a camera of an eXtended Reality (XR) device, wherein the camera of the XR device includes a first plurality of cameras which are arranged to face forward and a second plurality of cameras which are arranged to face downward; reproducing and displaying the image within a virtual golf environment displayed on a display unit of the XR device; capturing, in real-time, a golf swing of a user through the first plurality of cameras and the second plurality of cameras; analyzing a golf swing motion of the user in real-time using an artificial neural network model; and reproducing and displaying the analyzed golf swing motion within the virtual golf environment displayed on the display unit of the XR device.
Head tracking input arrangements · CPC title
using optical means · CPC title
worn on the head or face, e.g. combined with goggles or glasses · CPC title
Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills · CPC title
Golf · CPC title
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