Language-Based 3D Environment Construction for Interactive Video
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Solution Overview
Problem
Conventional artificial intelligence and reinforcement learning techniques are inaccurate, highly specific, and cumbersome for navigating and populating three-dimensional environments, failing to support interactive virtual environments that can be navigated by autonomous agents or avatars.
Innovation Solution
A computing system that uses a path embedding generator to create a path language representation of a three-dimensional virtual environment based on natural language input, incorporating entities and scripts for behavior, and renders a video of the environment using a large language model, enabling dynamic interaction and updating based on user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional artificial intelligence and reinforcement learning techniques are used for navigating three-dimensional environments, then specific navigation tasks can be performed, but the techniques are inaccurate, highly specific, and cumbersome to deploy
Solution Approach 1:
The patent uses neural radiance fields (NeRF) to create accurate three-dimensional representations by copying and reconstructing environmental geometry and appearance from multiple two-dimensional images. This allows the system to achieve high navigation accuracy without requiring complex manual modeling, thereby resolving the contradiction between precision and deployment complexity
Solution Approach 2:
The patent replaces traditional mechanical and algorithmic navigation systems with a learning-based approach using neural networks. The system learns navigation policies through reinforcement learning and executes them via neural field representations, substituting conventional mechanical control systems with intelligent, adaptive software-based control that is more accurate and easier to deploy
2Adaptability or versatility
If conventional artificial intelligence techniques are used, then specific tasks can be performed, but they fail to support generating interactive virtual environments that can be populated and navigated by autonomous agents
Solution Approach 1:
The patent creates a universal virtual environment generation system that can populate environments with diverse autonomous agents and support multiple navigation tasks simultaneously. The NeRF-based framework and learned navigation policies are generalizable across different scenarios, enabling the system to adapt to various tasks while maintaining reliable performance through consistent underlying mechanisms
Data Source
AI summary
A computing system may include a communication interface configured to receive from a first client machine a natural language description of a three-dimensional environment. A path embedding generator may determine a path language representation of a three-dimensional virtual environment based on the natural language description and via a large language model interface. The path language representation may be generated in accordance with a path language definition and may include one or more entities to include within the three-dimensional virtual environment. The path language representation may include a script governing behavior of the one or more entities and including one or more events. A video may be rendered based on the path representation.