Metaverse Abuse Reporting Overlay With Visible Avatar Selection
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Solution Overview
Problem
In virtual environments, it is difficult for moderators to gather evidence of avatar actions and dynamic content abuse due to lack of recording, making it challenging to address offensive behaviors effectively.
Innovation Solution
A system captures a 3D virtual experience, generates a 2D capture, determines a list of visible avatars using near-clip and far-clip planes, and creates an overlay for user-selectable abuse reporting, utilizing machine-learning for verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If 3D capture of virtual experience is performed, then comprehensive abuse detection capability is improved, but system complexity increases
Solution Approach 1:
The system extracts the essential information from the complex 3D virtual experience by generating a 2D capture that represents the user's field of view. This 2D representation contains sufficient abuse detection information while significantly reducing the data complexity and processing requirements compared to working with full 3D data.
Solution Approach 2:
The system creates a simplified copy (2D capture) of the 3D virtual experience that preserves the essential visual information needed for abuse detection. This copy maintains the field of view and visible avatars while reducing computational complexity for processing and analysis.
2Reliability
If list of all avatars is processed, then completeness of abuse detection is improved, but processing time increases
Solution Approach 1:
The system extracts only the avatars that are visible to the user within the field of view, excluding avatars that are not visible. This selective extraction maintains detection completeness for relevant abuse cases while significantly reducing the number of avatars that need processing, thereby decreasing processing time.
Solution Approach 2:
The system applies different processing quality to different avatars based on their visibility status. Visible avatars receive full processing for abuse detection, while invisible avatars are excluded from processing. This local differentiation optimizes the balance between detection completeness and processing efficiency.
3Ease of operation
If 2D capture with overlay is generated, then ease of user reporting is improved, but data processing complexity increases
Solution Approach 1:
The system creates a simplified 2D copy of the 3D scene that is easier for users to interpret and interact with. The overlay interface on the 2D capture provides clear visual indicators for selectable avatars, making the reporting process more intuitive while the 2D representation reduces the data processing complexity compared to working with full 3D data.
Data Source
AI summary
A metaverse application receives, from a user, a request to report abuse that occurs in a virtual experience. Responsive to receiving the request, the metaverse application captures a three-dimensional (3D) capture of the virtual experience. The metaverse application generates a two-dimensional (2D) capture from the 3D capture. The metaverse application determines a list of avatars in the 2D capture. The metaverse application mixes the additional audio with the encoded audio. The metaverse application generates a list of candidates from the list of avatars based on whether the avatars are visible to the user. The metaverse application generates graphical data for displaying an overlay on the 2D capture with the list of candidates that is user-selectable to provide a report of abuse.