AR Multi-Dimensional Model Generation from Point Clouds
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing augmented reality technologies require significant human effort and time to create multi-dimensional models and animations, and they cannot automatically place or track these models within an augmented reality environment, nor do they superimpose step-by-step 3D animated instructions, making them unsuitable for self-assist applications.
Innovation Solution
A system comprising a processor that annotates multi-dimensional point cloud representations of objects to generate multi-dimensional models, trains models to detect and segment components, and overlays these models onto physical objects in an augmented reality environment, enabling automatic multi-dimensional model generation and tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If human effort is used to create multi-dimensional models and animations, then model accuracy and quality are improved, but time consumption and labor requirements increase significantly
Solution Approach 1:
The system enables automatic self-service model generation by using machine learning algorithms to process point cloud data and generate 3D models without requiring manual human intervention for each modeling task, thus reducing time consumption while maintaining accuracy through automated processing
Solution Approach 2:
The patent replaces manual mechanical modeling processes with automated computational algorithms that process point cloud representations and generate multi-dimensional models automatically, substituting human labor with machine-based computational mechanisms
2Measurement precision
If manual placement and adjustment of multi-dimensional models is performed, then model positioning accuracy is improved, but operational complexity and time requirements increase
Solution Approach 1:
The system automatically performs model placement and positioning tasks without requiring manual intervention, using automated tracking algorithms to position multi-dimensional models in augmented reality environments while maintaining positioning accuracy through computational methods
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors and adjusts model positioning based on tracked object positions in the augmented reality environment, ensuring accurate placement through iterative feedback loops
3Extent of automation
If existing augmented reality technologies are used, then basic visualization is achieved, but automatic model generation, placement, and tracking capabilities are missing
Solution Approach 1:
The patent merges multiple functions including point cloud processing, machine learning model training, automatic model generation, placement, and tracking into a unified integrated system, combining previously separate capabilities into a single cohesive platform
Solution Approach 2:
The system is designed as a universal platform that can handle multiple tasks including visualization, automatic model generation, placement, tracking, and interaction within augmented reality environments, making the system multi-functional and adaptable to various applications
Data Source
AI summary
Systems, computer-implemented methods, and computer program products to facilitate automatic multi-dimensional model generation and tracking in an augmented reality environment are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise a label component that annotates a multi-dimensional point cloud representation of an object present in augmented reality data. The computer executable components further comprise a content generation component that generates a multi-dimensional model of a component of the object based on the multi-dimensional point cloud representation.