XR Real Object Transformation via 3D Model Segmentation
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Solution Overview
Problem
Existing XR technologies lack the ability to enable users to interactively and easily transform real-world objects in a customized manner, depending on the transformation purpose, which limits intuitive and efficient interaction within extended reality environments.
Innovation Solution
A method and apparatus that segment a target object from an input image, extract a similar target object from pre-learnt 3D model data, map the object's texture, and transform its shape based on user intention, allowing for real-time rendering and output of the transformed object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generic XR technologies are used for object transformation, then basic transformation functionality is achieved, but user interaction flexibility and customization capability are limited
Solution Approach 1:
The system segments the transformation process into distinct modules: object detection module, 3D model extraction module, texture mapping module, and shape transformation module. Each module handles a specific aspect of the transformation, allowing independent optimization and user customization without increasing overall system complexity.
Solution Approach 2:
The system implements dynamic transformation modes that adapt to user input in real-time. Users can interactively adjust transformation parameters such as shape, size, and orientation during the process, enabling flexible customization while maintaining system stability through structured control flow.
2Manufacturing precision
If detailed object transformation is implemented, then transformation precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing 3D model data in an optimized format before transformation is needed. Object features and geometric properties are pre-calculated and stored, enabling rapid retrieval and application during the transformation process without compromising accuracy.
Solution Approach 2:
The system replaces traditional mechanical transformation methods with computational approaches. Instead of physical manipulation, digital algorithms perform shape transformation, texture mapping, and rendering calculations, achieving high precision transformation with significantly reduced processing time through efficient computational geometry operations.
Data Source
AI summary
A method of providing a user-interactive customized interaction for a transformation of an extended reality (XR) real object includes segmenting a target object from an input image received through a camera, extracting a similar target object having a highest similarity to the target object from three-dimensional (3D) model data that has been previously learnt, extracting texture of the target object through the camera and mapping the texture to the similar target object, transforming a shape of the similar target object by incorporating intention information of a user based on a user interaction, and rendering and outputting the transformed similar target object.