Virtual Reality Private-Item Detection for Access Control
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Solution Overview
Problem
Existing virtual reality systems lack effective methods to protect users' privacy within virtual environments, particularly in identifying and managing private items that should not be accessible to all users.
Innovation Solution
A method and system for transmitting notifications of identified private items in a virtual environment's data feed, utilizing a plurality of detection models associated with various private items, to ensure that only authorized users can access these items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple detection models are applied to identify private items in the virtual environment, then privacy protection capability is improved, but system complexity increases
Solution Approach 1:
The system segments privacy protection into multiple specialized detection models, each trained to identify specific types of private items (e.g., documents, personal belongings, sensitive areas). This segmentation allows comprehensive privacy coverage while keeping each individual model manageable and interpretable, resolving the contradiction between thorough privacy protection and system complexity.
Solution Approach 2:
The detection models are trained in advance on extensive datasets containing various private items before deployment. This preliminary training action enables the models to automatically recognize and flag private items during runtime without requiring complex real-time analysis, thereby improving privacy protection while maintaining operational simplicity.
2Reliability
If detection models continuously monitor the data feed for private items, then privacy security is improved, but computational energy consumption increases
Solution Approach 1:
The system implements periodic monitoring where detection models analyze the data feed at scheduled intervals rather than continuously. This periodic action maintains privacy security by regularly scanning for private items while significantly reducing computational energy consumption compared to uninterrupted monitoring, directly resolving the identified contradiction.
Solution Approach 2:
The detection models rapidly scan through the data feed during monitoring cycles, quickly identifying and flagging private items before moving to the next segment. This rushing through approach ensures comprehensive coverage for privacy security while minimizing the time each frame spends in computation, thereby reducing overall energy consumption.
Data Source
AI summary
A processing system including at least one processor may obtain a list of a plurality of private items associated with a region of a virtual environment, obtain a data feed of the region of the virtual environment, apply the data feed as an input to a plurality of detection models associated with the plurality of private items, identify at least one of the plurality of private items in the data feed via at least one output of at least one of the plurality of detection models, and transmit a notification to at least one entity that the at least one of the plurality of private items is identified in the data feed.