Volumetric Object Tagging for Cross-Environment AR Scaling
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Solution Overview
Problem
There is no coherent system for translating between fully virtual and partially physical and partially virtual environments, making it difficult for creators to share AR environments of varying sizes and layouts without tedious manual rescaling of volumetric objects.
Innovation Solution
A system that tags volumetric objects with metadata defining spatial relationships, allowing automatic scaling and repositioning to fit different environments, using identification, tagging, detection, and adjustment modules to maintain consistent display across varying AR environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If volumetric objects are manually rescaled to fit different AR environments, then spatial compatibility is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary actions by automatically detecting environment dimensions and pre-calculating appropriate scaling factors for volumetric objects before the user needs to use them. The tagging system prepares objects with metadata that enables automatic adaptation, eliminating the need for manual rescaling when objects are transferred between environments.
Solution Approach 2:
Volumetric objects are equipped with automated self-adjustment capabilities through metadata tags that enable them to automatically scale and adapt to different AR environments without requiring manual intervention. The system serves itself by automatically detecting environmental constraints and adjusting object properties accordingly.
2Productivity
If automatic scaling systems are implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent introduces metadata tags as an intermediary layer between volumetric objects and the AR environment. These tags contain scaling and spatial relationship information that mediate the interaction between objects and environments, enabling automatic adaptation without requiring complex real-time calculation systems or sophisticated device hardware.
Solution Approach 2:
The system manages complexity by changing parameters in a controlled manner through predefined metadata tags that specify scaling factors and spatial relationships. Rather than implementing complex adaptive algorithms, the system uses parameter-based control where objects carry information about how they should be scaled and positioned, simplifying the overall system architecture.
Data Source
AI summary
A computer-implemented method for matching volumetric objects to artificial reality environments may include (i) identifying a volumetric object created within an artificial reality environment and an original spatial relationship between the volumetric object and the artificial reality environment, (ii) applying a tag to the volumetric object that defines an aspect of a spatial relationship between the volumetric object and any environment in which the volumetric object is positioned, (iii) detecting that the volumetric object is positioned in an environment that is not compatible with the original spatial relationship between the volumetric object and the artificial reality environment in which the volumetric object was created, and (iv) adjusting the aspect of the spatial relationship between the volumetric object and the environment based on the tag that defines the aspect of the spatial relationship between the volumetric object and the environment. Various other methods, systems, and computer-readable media are also disclosed.