AI-Based Virtual Asset Composition Through Editable Image Layers
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Solution Overview
Problem
Existing video game development processes lack efficient tools for creating and refining virtual assets, limiting the ability to enhance gameplay experience and player engagement.
Innovation Solution
An AI-based system for interactive virtual asset composition that includes an input processor, AI-based image generation, layer extraction, auto-completion, and refinement, enabling automatic and user-directed editing of graphical content layers within a composite image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual methods are used for creating and editing virtual assets, then designers have full control over each detail, but the process is time-consuming and reduces productivity
Solution Approach 1:
The patent segments a composite image into multiple editable layers using AI-based layer extraction. Each layer represents a distinct graphical content element that can be independently processed, edited, and refined. This segmentation enables parallel processing of different asset components, significantly improving productivity while maintaining design control.
Solution Approach 2:
The patent replaces manual mechanical editing processes with AI-based automated systems. The AI performs layer extraction, auto-completion, and refinement tasks that would otherwise require time-consuming manual work. This substitution dramatically reduces time-to-market while preserving designer oversight through the workbench interface.
2Productivity
If AI-based automated systems are used for virtual asset creation, then productivity increases and time-to-market decreases, but the complexity of the system increases
Solution Approach 1:
The patent employs a multi-functional AI system that performs multiple tasks: generating base images, extracting layers, auto-completing content, and refining assets. This universal system handles diverse virtual asset creation tasks through a single integrated platform, managing complexity by consolidating functions rather than requiring separate tools for each operation.
Solution Approach 2:
The layer editing workbench serves as an intermediary interface between the complex AI processing system and the designer. It provides a simplified control layer that manages the complexity of underlying AI operations, allowing designers to interact with the system through intuitive commands while the AI handles the complex automated processing in the background.
3Manufacturing precision
If AI-based layer extraction and auto-completion are used, then manufacturing precision of virtual assets improves, but the extent of automation increases system complexity
Solution Approach 1:
The patent applies preliminary AI-based actions to prepare virtual assets for final use. The system pre-extracts layers, pre-completes graphical content, and pre-refines assets according to specified criteria. These preliminary automated actions ensure high manufacturing precision by systematically applying quality improvements before the asset is finalized, reducing the need for manual refinement.
Solution Approach 2:
The layer editing workbench implements feedback mechanisms that allow designers to review and adjust AI-generated layers. The system provides automated extraction and completion results that can be examined, modified, and refined through the workbench interface. This feedback loop ensures high visual quality by combining AI precision with human oversight, managing automation extent through iterative refinement.
Data Source
AI summary
A base image is generated by an artificial intelligence (AI)-based image generation system based on a user-specified input specification. An AI-based image layer extraction system automatically identifies and extracts a plurality of layers of graphical content within the base image into a corresponding plurality of pre-layer images. An AI-based image auto-complete system automatically completes each of the plurality of pre-layer images into a corresponding plurality of full-layer images respectively corresponding to the plurality of layers of graphical content within the base image. A layer editing workbench controller provides for display and user-directed editing of a selected one or more of the plurality of full-layer images. An AI-based composite image generator automatically combines the plurality of full-layer images as edited by the layer editing workbench controller into a composite image.