20240053819. SYSTEMS AND METHODS FOR VIRTUAL AND AUGMENTED REALITY simplified abstract (Magic Leap, Inc.)

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SYSTEMS AND METHODS FOR VIRTUAL AND AUGMENTED REALITY

Organization Name

Magic Leap, Inc.

Inventor(s)

Eric C. Browy of Meridian ID (US)

SYSTEMS AND METHODS FOR VIRTUAL AND AUGMENTED REALITY - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240053819 titled 'SYSTEMS AND METHODS FOR VIRTUAL AND AUGMENTED REALITY

Simplified Explanation

The patent application describes systems and methods for distributed computing and networking for mixed reality systems. It involves capturing images and inertial data using a head-wearable device, estimating the device's position based on the captured data, transmitting the image to a remote server, training a neural network based on the image, and transmitting the trained neural network back to the device.

  • The method involves capturing images and inertial data using a camera and an inertial measurement unit of a head-wearable device.
  • The position of the device is estimated based on the captured image and inertial data using one or more processors of the device.
  • The captured image is transmitted to a remote server.
  • A neural network is trained based on the image using the remote server.
  • The trained neural network is transmitted back to the head-wearable device.

Potential Applications:

  • Mixed reality systems: The technology can be used in mixed reality systems to enhance the user experience by capturing and processing images and inertial data.
  • Remote training: The remote server can train neural networks based on the captured images, allowing for remote training of AI models.
  • Real-time tracking: The estimation of the device's position based on the captured data can be used for real-time tracking in various applications, such as gaming or navigation.

Problems Solved:

  • Processing limitations: By offloading the image processing and neural network training to a remote server, the head-wearable device can overcome processing limitations and perform complex tasks.
  • Training limitations: The remote training capability allows for training neural networks on more powerful servers, enabling more accurate and efficient models.
  • Real-time tracking accuracy: The combination of image and inertial data allows for more accurate estimation of the device's position, improving real-time tracking accuracy.

Benefits:

  • Enhanced user experience: The technology enables more immersive and interactive experiences in mixed reality systems.
  • Improved performance: By utilizing distributed computing and networking, the system can achieve better performance and handle more computationally intensive tasks.
  • Remote training flexibility: The ability to train neural networks remotely provides flexibility and scalability in AI model development.


Original Abstract Submitted

disclosed herein are systems and methods for distributed computing and/or networking for mixed reality systems. a method may include capturing an image via a camera of a head-wearable device. inertial data may be captured via an inertial measurement unit of the head-wearable device. a position of the head-wearable device can be estimated based on the image and the inertial data via one or more processors of the head-wearable device. the image can be transmitted to a remote server. a neural network can be trained based on the image via the remote server. a trained neural network can be transmitted to the head-wearable device.

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