Natural Language 3D Scene Generation System
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Solution Overview
Problem
Conventional systems for creating three-dimensional digital content require significant training and are inefficient, even for skilled users, due to the complexity and multitude of tools needed to generate high-quality three-dimensional scenes.
Innovation Solution
A natural-language based three-dimensional modeling system that generates three-dimensional scenes by analyzing natural language requests, converting them into entity-command representations, and mapping these to existing semantic scene graphs to select and modify three-dimensional scenes from a database, thereby simplifying the process and improving accessibility and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional software applications with multiple tools are used to create three-dimensional scenes, then high-quality three-dimensional content can be generated with customization and precision, but the system complexity increases and requires significant training
Solution Approach 1:
The patent introduces a natural language processing intermediary that translates user-friendly natural language commands into the complex operations required by the three-dimensional modeling system. This mediator layer allows users to express intentions in simple language while the system handles the underlying complexity of tool selection, parameter adjustment, and scene generation automatically.
Solution Approach 2:
The system performs self-service by automatically selecting appropriate tools and operations based on the natural language request, generating three-dimensional scenes without requiring manual intervention for tool configuration. The system handles its own complexity internally while presenting a simplified interface to the user.
2Ease of operation
If conventional systems with multiple control menus are used, then detailed control over three-dimensional content is achieved, but the time required to navigate interfaces increases
Solution Approach 1:
The patent replaces the mechanical navigation process of moving through menus and interfaces with an automated natural language processing system. Instead of manually traversing hierarchical controls, users simply speak or type their intentions, and the system interprets and executes the corresponding three-dimensional scene generation operations directly.
3Adaptability or versatility
If conventional systems require learning multiple tools and operations, then comprehensive functionality is achieved, but the barrier to entry for new users increases
Solution Approach 1:
The natural language processing intermediary serves as an accessible entry point that translates everyday language into system commands. This mediator eliminates the need for users to learn specialized tool names, menu structures, or operational syntax, while still providing access to the full range of three-dimensional scene generation capabilities.
Solution Approach 2:
The system achieves universality by using a single natural language interface to control diverse three-dimensional scene generation tasks. Rather than requiring separate interfaces or tools for different functions, the system handles all operations through a unified language-based interaction model.
Data Source
AI summary
Methods, systems, and non-transitory computer readable storage media are disclosed for generating a three-dimensional scene based on a natural language phrase. For example, the disclosed system can analyze a natural language phrase to determine dependencies involving entities and commands in the natural language phrase. The disclosed system can then use the dependencies to generate an entity-command representation of the natural language phrase. Additionally, the disclosed system can generate a semantic scene graph for the natural language phrase from the entity-command representation to indicate contextual relationships of the entities and commands. Furthermore, the disclosed system generates the requested three-dimensional scene by using at least one scene of a plurality of available three-dimensional scenes identified using the semantic scene graph of the natural language phrase.