Primary And Secondary Viewer Detection for Unauthorized Playback Control
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Solution Overview
Problem
Existing content rating systems do not account for individual viewer preferences and cannot effectively prevent unsuitable content from being viewed by unauthorized viewers, particularly young children.
Innovation Solution
A reaction detection system that uses machine learning and sensors to identify primary and secondary viewers, detecting reactions to modify content playback or output alternative content based on predefined criteria, such as the presence of unauthorized viewers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a broad based content rating system is used, then content suitability is determined for general audiences, but it cannot meet the needs of individual viewers or prevent unauthorized viewing by children
Solution Approach 1:
The system performs preliminary actions by detecting the presence of viewers and identifying primary versus secondary viewers before content playback occurs. This allows the system to proactively determine appropriate content restrictions rather than reacting after unauthorized viewing has begun
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring viewer presence and reactions during content playback. When a secondary viewer is detected or when adverse reactions are observed, the system adjusts content output accordingly, creating a closed-loop control system that adapts to real-time conditions
2Reliability
If content playback is continuously monitored for viewer reactions, then unauthorized viewing can be detected and prevented, but system complexity and processing requirements increase
Solution Approach 1:
The system employs self-service principles by utilizing the device's existing sensors (camera, microphone, motion detectors) to perform viewer detection and reaction analysis. This eliminates the need for separate dedicated detection hardware, reducing overall system complexity while maintaining reliable monitoring capabilities
Solution Approach 2:
The system replaces complex mechanical or manual viewer verification methods with automated sensor-based detection and machine learning algorithms. This substitution enables reliable detection of viewer presence and reactions through optical and acoustic fields rather than physical interaction
3Reliability
If the system detects and responds to secondary viewers, then content protection is improved, but response time and processing speed may be reduced
Solution Approach 1:
The system applies partial action by selectively responding to specific conditions rather than continuously interrupting playback. It only modifies content output when adverse reactions are detected or when secondary viewers are identified, allowing uninterrupted playback during normal viewing conditions while maintaining protection effectiveness
Data Source
AI summary
Systems, apparatuses, and methods for detecting the reactions of primary and secondary viewers of content are described. Reactions of a primary or secondary viewer of content may be detected through use of a sensor and machine learning model. Based on the reaction of the primary or secondary viewer satisfying some criteria, outputting of the content may be modified and/or alternative content may be provided. Furthermore, metadata may be generated based on the detection of adverse reactions to intrusions by a viewer of content that is associated with an indication that the outputted content is associated with certain predefined types.