Automated Object Labeling in Extended Reality via Vision Algorithms
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Solution Overview
Problem
In extended reality environments, manual labeling of objects in real environments for interaction is inefficient and prone to errors, affecting the accuracy of virtual object interactions and model construction.
Innovation Solution
An extended reality-based control method and apparatus that uses vision algorithms to automatically identify corner points and edge lines of target objects in environment images, enabling automatic labeling and reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual labeling is used for target objects in extended reality environments, then users can directly label objects, but the labeling process is inefficient and prone to errors
Solution Approach 1:
The patent replaces manual mechanical labeling operations with automated vision-based detection systems. The system uses image processing algorithms to automatically identify corner points and edge lines of target objects, substituting human manual labeling with automated computational methods, thereby improving both efficiency and accuracy
Solution Approach 2:
The system enables self-service automated labeling by having the environment automatically detect and label target objects through vision algorithms. The corner point detection and edge line identification processes occur without human intervention, allowing the system to autonomously complete the labeling task
2Productivity
If automated vision algorithms are used for labeling, then labeling efficiency and accuracy are improved, but system complexity increases
Solution Approach 1:
The patent segments the automated labeling system into distinct functional modules: image acquisition module, corner point detection module, edge line detection module, and labeling module. This segmentation allows each module to perform a specific function independently, making the overall complex system more manageable and maintainable while achieving high labeling efficiency
Data Source
AI summary
The disclosure provides an extended reality-based control method, apparatus, electronic device and storage medium. The extended reality-based control method comprises: obtaining an environment image of a real environment; identifying a corner point and/or an edge line of a target object in the environment image based on a vision algorithm; and automatically labeling the target object in the environment image based on the identified corner point and/or edge line.