Semantic 3D Asset Recommendations for VR World-Building Workflows

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Solution Overview

Problem

The process of searching for and selecting 3D assets in virtual reality (VR) environments for 3D world-building is cumbersome and inefficient, often requiring tedious manual input and lacking tools for recommending relevant assets based on real-time changes, leading to a time-consuming and unintuitive workflow.

Innovation Solution

A system utilizing machine learning models to generate natural language descriptions of the 3D environment and recommend relevant 3D objects based on semantic understanding, providing an intuitive interface for users to seamlessly integrate assets into the VR environment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If users manually search and select 3D assets in VR environments, then they can find and import assets, but the process becomes time-consuming and cumbersome

Engineering Contradiction:

Improveasset selection efficiencyVSAvoidtime spent searching for assets

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system automatically analyzes the 3D environment and generates asset recommendations without requiring manual user input. The AI-powered interface performs visual processing of the environment, determines context, and queries the content library autonomously to provide relevant asset suggestions, allowing the system to serve itself in the asset recommendation process

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system continuously monitors and analyzes the 3D environment in real-time, pre-computing context information and maintaining an updated understanding of the scene. This preliminary analysis enables the system to immediately provide relevant asset recommendations when needed, rather than requiring time-consuming searches at the moment of need

Inventive Principle:

Principle #10Preliminary action

2Ease of operation

If users type search queries in VR interfaces, then they can search for specific assets, but the workflow is interrupted and focus is lost

Engineering Contradiction:

Improveworkflow continuityVSAvoidinterface interaction complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system replaces manual typing and menu navigation with AI-powered automated analysis. Instead of requiring users to mechanically type search queries and navigate interfaces, the system uses visual processing and natural language generation to understand the environment and provide recommendations, substituting the mechanical interaction process with an intelligent automated system

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The AI-powered user interface acts as an intermediary between the user's intent and the 3D content library. Rather than requiring direct user interaction with search fields and asset lists, the AI mediator automatically interprets the environment, formulates appropriate queries, and presents relevant results, simplifying the interaction process

Inventive Principle:

Principle #24Intermediary (Mediator)

3Adaptability or versatility

If comprehensive 3D asset libraries are provided, then users have more asset choices, but it becomes difficult to find relevant assets among the overwhelming number

Engineering Contradiction:

Improveasset selection relevanceVSAvoidrelevance identification difficulty

Core Design Contradiction:

Adaptability or versatilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system continuously analyzes the 3D environment and updates its understanding of the scene context as assets are added or modified. This feedback loop allows the system to adapt its recommendations based on the current state of the environment, ensuring that suggested assets remain relevant to the overall scene and design intent

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system dynamically adjusts its search and recommendation parameters based on the analyzed context of the 3D environment. By changing the parameters of asset selection based on environmental factors such as scene theme, existing assets, and spatial relationships, the system can effectively navigate large asset libraries and identify relevant assets without requiring manual filtering

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12633049B2Systems and methods for providing semantics-based recommendations for three-dimensional content creation

Publication Date: 2026.05.19 ADEIA GUIDES INC

AI summary

Systems and methods are described for providing for display a user interface to facilitate creation of a three-dimensional (3D) environment. The disclosed techniques may generate the 3D environment based on one or more inputs received via the user interface, and perform visual processing of the 3D environment to obtain a natural language description of the 3D environment. The disclosed techniques may determine a context of the 3D environment based at least in part on the natural language description and may store the context in a data structure. A 3D content library may be queried, based on the natural language description of the 3D environment, to identify at least one recommended 3D object that is relevant to the stored context of the 3D environment. The disclosed techniques may providing for display, at the user interface, selectable option(s) to add the at least one recommended 3D object to the 3D environment.