Mapping Virtual Assets to Physical Boundaries Using GAN Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Augmented and virtual reality systems face challenges in effectively mapping virtual environments within the confines of physical location boundaries, leading to cumbersome and impractical user experiences due to size limitations and physical space constraints.
Innovation Solution
The use of Generative Adversarial Networks (GAN) to optimize the placement and scaling of virtual assets within physical spaces, integrating physical boundaries and obstacles, and classifying assets as point of interest or filler assets to create seamless and optimized virtual environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If virtual environments are mapped to real-world physical locations, then user immersion and experience quality improve, but physical space constraints and size limitations worsen the mapping process
Solution Approach 1:
The system segments virtual assets into two categories: POI (Point of Interest) assets that are manually placed at specific locations, and filler assets that are automatically generated using GAN to fill remaining spaces. This segmentation allows the system to handle both important and non-important virtual elements differently, optimizing the mapping process within physical constraints.
Solution Approach 2:
The system uses Generative Adversarial Networks to generate synthetic filler assets that copy the visual style and characteristics of real-world objects. These generated assets are used to populate remaining spaces in the virtual environment, creating a complete mapping without requiring physical space for every virtual element.
2Quantity of substance
If more virtual assets are placed in the virtual environment, then the completeness and detail of the virtual space improve, but the complexity of mapping and space management worsens
Solution Approach 1:
The system divides virtual assets into POI assets (manually placed) and filler assets (automatically generated). This segmentation reduces mapping complexity by automating the placement of non-critical assets through GAN generation, while maintaining control over important POI elements.
Solution Approach 2:
The GAN-based filler asset generation system automatically creates and places virtual assets without requiring manual intervention. The system serves itself by generating appropriate filler content based on the virtual environment's requirements, reducing the overall mapping complexity.
3Reliability
If physical boundaries are strictly enforced to contain virtual environments, then safety and spatial awareness improve, but the immersion and freedom of exploration worsen
Solution Approach 1:
The system applies different qualities to different regions of the virtual environment. POI assets are placed at specific locations with precise positioning, while filler assets are generated to adapt to available spaces. This local differentiation allows the system to maintain spatial containment while creating varied exploration opportunities within boundaries.
Data Source
AI summary
Systems, methods, and computer programming products for generating, rendering and/or displaying a computer-generated virtual environment as augmented reality and/or virtual reality. The physical boundaries containing the active area where the virtual environments are rendered and displayed are established. Based on the constraints and characteristics of the physical boundaries, virtual environments are mapped using assets from real, historical and/or fictitious locations. The assets can be dynamically re-sized and distanced to fit constraints of the physical space. Based on historical levels of interactivity with the selected environments, the virtual assets can be sorted and tagged as points of interest or filler assets, then mapped to the virtual environment using GAN technology and other machine learning techniques to re-create unique versions of the selected environments. Virtual thresholds can be introduced to segment the virtual environment into multiple portions and reduce the amount of assets needing to be simultaneously displayed.