Neural Network Terrain Generation System
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Solution Overview
Problem
The process of creating 3D terrain for video game worlds is time-consuming and inefficient, as developers must manually incorporate and modify LIDAR data to match the game world, lacking an effective method for rapid and efficient generation of realistic terrain.
Innovation Solution
A system and method that uses a graphical user interface to generate game terrain data by inputting user-drawn graphical inputs into a neural network trained on LIDAR data, producing a height field and applying terrain styles, including biome-specific landform details, to create realistic and efficient 3D terrain models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual methods are used to incorporate and modify LIDAR data to create 3D terrain, then terrain can be created with realistic detail, but the process becomes extremely time-consuming and inefficient
Solution Approach 1:
The patent introduces an intermediary system consisting of a neural network and processing algorithms that automatically transform raw LIDAR data into game-ready 3D terrain. This intermediary automation layer resolves the contradiction by eliminating manual manipulation while preserving realistic terrain generation through AI-driven processing of elevation data, normal maps, and biome classification.
Solution Approach 2:
The patent replaces the mechanical manual process of terrain creation with an automated computational system. Instead of developers manually adjusting LIDAR data points and terrain parameters, the system uses machine learning models and algorithms to automatically generate realistic 3D terrain from raw data, substituting human labor with intelligent automation that maintains high realism standards.
2Ease of operation
If manual terrain creation methods are used, then developers have full control over terrain details, but the complexity and time required increases significantly
Solution Approach 1:
The patent implements self-service automation where the system automatically performs terrain generation, classification, and optimization tasks without requiring manual intervention. The neural network autonomously processes LIDAR data, identifies biome regions, generates appropriate terrain features, and optimizes the output for game engines, dramatically simplifying the operator's task while reducing overall process complexity through intelligent automation.
3Manufacturing precision
If LIDAR data is used to generate 3D terrain models, then realistic terrain can be achieved, but manual modification is required to match game world requirements
Solution Approach 1:
The patent applies preliminary action by pre-processing LIDAR data through neural network classification to identify and label different biome regions (forests, deserts, mountains, etc.) before terrain generation. This preliminary classification enables the system to automatically apply appropriate terrain features and vegetation patterns matched to game world requirements, eliminating the need for time-consuming manual modifications while maintaining high accuracy.
Solution Approach 2:
The patent dynamically changes terrain parameters such as elevation, slope, vegetation density, and biome classification based on the analyzed LIDAR data characteristics. The system automatically adjusts these parameters to match game world requirements through AI-driven optimization, resolving the contradiction by maintaining terrain accuracy while eliminating manual parameter adjustment time.
Data Source
AI summary
Embodiments of the systems and methods described herein provide game terrain generation system that can generate height field data from a sketch of graphical inputs from a user via a graphical user interface. The game terrain generation system can use a model, such as a trained neural network, to apply macro and micro topological features on top of the height field data to generate game terrain data. The game terrain generation system can identify boundaries between different styles of terrain and generate transitions between the styles to create a more realistic terrain boundary.