Samsung electronics co., ltd. (20240129448). METHOD AND SYSTEM FOR CONVERTING SINGLE-VIEW IMAGE TO 2.5D VIEW FOR EXTENDED REALITY (XR) APPLICATIONS simplified abstract

METHOD AND SYSTEM FOR CONVERTING SINGLE-VIEW IMAGE TO 2.5D VIEW FOR EXTENDED REALITY (XR) APPLICATIONS

Organization Name

samsung electronics co., ltd.

Inventor(s)

Yingen Xiong of Mountain View CA (US)

Christopher A. Peri of Mountain View CA (US)

METHOD AND SYSTEM FOR CONVERTING SINGLE-VIEW IMAGE TO 2.5D VIEW FOR EXTENDED REALITY (XR) APPLICATIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240129448 titled 'METHOD AND SYSTEM FOR CONVERTING SINGLE-VIEW IMAGE TO 2.5D VIEW FOR EXTENDED REALITY (XR) APPLICATIONS

Simplified Explanation

The method described in the abstract involves using machine learning models to generate texture maps and depth maps for different imaging sensor poses, ultimately creating a stereo image pair representing a 2.5D view of a 2D image captured by an imaging sensor. This stereo image pair is then displayed on an XR device.

• Obtaining a 2D image captured by an imaging sensor
• Providing the 2D image, imaging sensor pose, and additional sensor poses to a machine learning model
• Generating texture maps and depth maps for each sensor pose
• Creating a stereo image pair based on the texture and depth maps
• Displaying the stereo image pair on an XR device

Potential Applications

This technology could be applied in various fields such as virtual reality, augmented reality, 3D modeling, and computer vision.

Problems Solved

This technology solves the problem of creating a 3D representation from a 2D image captured by an imaging sensor, allowing for more immersive and realistic visualizations.

Benefits

The benefits of this technology include enhanced visualization capabilities, improved depth perception, and a more interactive user experience in XR environments.

Potential Commercial Applications

Potential commercial applications of this technology include XR gaming, virtual tours, architectural visualization, medical imaging, and industrial training simulations.

Possible Prior Art

One possible prior art for this technology could be the use of machine learning models to generate depth maps and texture maps for 3D reconstruction in computer vision applications.

How does this technology impact the development of XR devices?

This article does not delve into the specific impact of this technology on the development of XR devices. It would be interesting to explore how the integration of 2.5D views generated by machine learning models can enhance the user experience and functionality of XR devices.

What are the potential limitations of using machine learning models for generating texture and depth maps in this context?

The article does not address any potential limitations or challenges associated with using machine learning models for generating texture and depth maps. It would be valuable to investigate issues such as accuracy, computational resources, and training data requirements in implementing this technology.

Original Abstract Submitted

a method includes obtaining a 2d image captured using an imaging sensor. the 2d image is associated with an imaging sensor pose. the method also includes providing the 2d image, the imaging sensor pose, and one or more additional imaging sensor poses to at least one machine learning model that is trained to generate a texture map and a depth map for the imaging sensor pose and each additional imaging sensor pose. the method further includes generating a stereo image pair based on the texture maps and the depth maps. the stereo image pair represents a 2.5d view of the 2d image. the 2.5d view includes a pair of images each including multiple collections of pixels and, for each collection of pixels, a common depth associated with the pixels in the collection of pixels. in addition, the method includes initiating display of the stereo image pair on an xr device.