3D Object Models with Automated Metadata Integration from 2D Images
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Solution Overview
Problem
Conventional 2D to 3D modeling techniques lack metadata integration, requiring manual and costly processes to embed additional information into 3D object models, which is inconvenient for user experience and application in digital twin and metaverse environments.
Innovation Solution
A method to automatically generate customizable 3D model metadata by combining a first 3D object model with metadata acquired from databases and the Internet, using AI algorithms like NeRF for visualization and object detection to integrate metadata during the modeling process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional 2D to 3D modeling techniques are used, then visual 3D object models can be created, but metadata integration is lacking and requires manual processes
Solution Approach 1:
The system automatically performs metadata integration by itself without human intervention. The metadata extraction module automatically extracts metadata from 2D images, and the metadata integration module automatically integrates this metadata with the 3D object model, making the system self-sufficient in handling metadata integration tasks
Solution Approach 2:
The patent replaces manual mechanical operations with automated computational processes. Instead of manually extracting and integrating metadata, the system uses automated modules with algorithms to perform these tasks, substituting human labor with machine-based automated processing
2Loss of information
If manual metadata integration is performed, then comprehensive metadata can be added to 3D models, but labor and time costs increase significantly
Solution Approach 1:
The system performs metadata extraction from 2D images before the 3D modeling process begins. By preparing and organizing metadata in advance through automated extraction, the system ensures metadata completeness is achieved without adding time costs during the main modeling and integration phases
3Adaptability or versatility
If manual metadata integration is used, then 3D models can have embedded metadata, but user flexibility and efficiency in editing are reduced
Solution Approach 1:
The system provides dynamic and flexible metadata integration capabilities that allow users to easily modify, add, or remove metadata from 3D object models. The automated integration framework is designed to be adaptable, enabling efficient editing operations while maintaining high productivity through its automated nature
Data Source
AI summary
Embodiments of the present disclosure relate to a method, a device, and a computer program product for generating a three-dimensional (3D) object model. The method includes generating a first 3D object model based on multiple two-dimensional (2D) images of an object in different views. The method further includes acquiring metadata related to the first 3D object model by searching for information related to the object in at least one of a database and the Internet. The method further includes generating a second 3D object model by combining the first 3D object model and the metadata. The method for generating a 3D object model according to the present disclosure can automatically generate customizable and editable 3D model metadata, thereby significantly reducing labor, saving costs, improving efficiency, and improving user experience.