CGR Recording Content Restriction via Object Segmentation
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Solution Overview
Problem
Current computer-generated reality (CGR) systems lack effective mechanisms to restrict and manage content based on user profiles and privacy preferences, leading to potential unauthorized access to sensitive or protected information within CGR recordings.
Innovation Solution
A CGR system that analyzes recordings to identify protected content and user profiles, allowing for segmentation and modification of the recordings to filter or obscure restricted components, ensuring that only authorized users can access sensitive information during playback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CGR recordings include all captured content without restrictions, then complete information is preserved, but unauthorized access to sensitive information occurs
Solution Approach 1:
The system segments CGR recordings by identifying and separating protected content from non-protected content using object detection and user profile analysis. This allows selective application of restrictions to specific portions of the recording while preserving access to other content, resolving the contradiction between security and accessibility.
Solution Approach 2:
The system applies different access restrictions to different regions or objects within the CGR recording based on their sensitivity classification. Protected objects receive obfuscation or access controls while non-protected objects remain fully accessible, enabling localized security measures that preserve overall information accessibility.
2Reliability
If the system applies strict access restrictions to all content, then privacy protection is enhanced, but user experience and content usability deteriorate
Solution Approach 1:
The system applies restrictions selectively rather than universally - only to content identified as protected based on user profiles and sensitivity analysis. This partial application of restrictions maintains privacy protection for sensitive content while avoiding unnecessary limitations on usable content, thus preserving content usability.
Solution Approach 2:
Different quality levels of access are provided to different users based on their profiles and relationships to content subjects. Authorized users receive full-quality access to relevant content while maintaining privacy protections, ensuring ease of operation for legitimate users while protecting privacy.
3Measurement precision
If the system analyzes and modifies recordings to restrict content, then access control accuracy improves, but processing time and system complexity increase
Solution Approach 1:
The system performs preliminary analysis during the recording phase to identify and tag protected content based on user profiles and sensitivity detection. This pre-processing enables faster playback with pre-determined restrictions, improving access control accuracy while reducing real-time processing time demands.
Solution Approach 2:
The system creates modified copies of CGR recordings with embedded restriction metadata rather than altering the original recording. This copying approach enables accurate access control through metadata filtering while keeping processing time minimal, as the restrictions are applied through data layer modifications rather than extensive video processing.
Data Source
AI summary
Implementations of the subject technology provides analyzing a recording of content within a field of view of a device, the analyzing including recognition of a set of objects included in the content. The subject technology identifies a subset of the set of objects that are indicated as corresponding to protected content. The subject technology generates a modified version of the recording that obfuscates or filters the subset of the set of objects. Additionally, the subject technology provides the modified version of the recording to a host application for playback.