Shared Viewing Reaction Composition for Synchronized User Responses
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Solution Overview
Problem
Existing shared content viewing systems fail to capture and synchronize users' physical reactions during synchronized media consumption, limiting the engagement and interaction among participants.
Innovation Solution
A system and method that detects synchronized physical reactions of multiple users, generates visual content representing these reactions, and outputs a composition for presentation, enhancing user engagement and interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If synchronized content viewing is implemented, then users can consume media together remotely, but user physical reactions cannot be captured or shared
Solution Approach 1:
The system proactively captures physical reactions using cameras and sensors during the viewing session before the viewing concludes. By预先 detecting facial expressions, body movements, and physiological signals throughout the content playback, the system ensures reaction data is collected in real-time rather than attempting to retrieve it afterward.
Solution Approach 2:
The system creates visual copies of users' physical reactions by capturing images and video footage of facial expressions and body language. These visual copies are then processed through AI analysis to generate reaction indicators that are shared with other participants, effectively replicating the physical reaction experience across remote devices.
2Adaptability or versatility
If physical reaction detection is added to shared viewing system, then user engagement can be enhanced, but system complexity increases
Solution Approach 1:
The system employs multi-functional components that serve multiple purposes. For example, the camera array captures both the visual content being viewed and the users' physical reactions simultaneously. The same processing pipeline that handles content delivery also processes reaction data, and the AI model performs both content analysis and reaction detection, reducing the need for separate dedicated systems.
Solution Approach 2:
The system introduces an AI-based reaction analysis model as an intermediary layer between raw sensor data and shared reaction indicators. This intermediary automatically processes complex physical reaction data into simplified, shareable visual indicators, managing the complexity burden rather than requiring direct complex processing between all system components.
3Ease of operation
If visual content representing physical reactions is generated and shared, then interaction among participants is improved, but data processing requirements increase
Solution Approach 1:
The system extracts only the most salient and meaningful physical reaction features from the full set of captured data. Rather than processing and sharing all raw sensor data, the AI model identifies and extracts key reaction indicators such as facial expression changes, significant body movements, and physiological signals, reducing the data volume that needs to be processed and transmitted while maintaining interaction quality.
4Loss of time
If real-time reaction capture is implemented, then synchronized engagement is achieved, but detection precision requirements increase
Solution Approach 1:
The system performs preliminary calibration and baseline establishment before the actual viewing session begins. By capturing users' neutral states and typical movement patterns in advance, the system creates reference profiles that enable more accurate real-time detection during the viewing session, reducing the precision burden during actual reaction capture.
Data Source
AI summary
In one aspect, an example method in connection with a shared content viewing session in which multiple users are receiving and viewing respective instances of the same media content in a synchronized manner is disclosed. The example method includes (i) detecting that each of the multiple users respectively exhibits a threshold extent of physical reaction around the same time; (ii) responsive to the detecting, for each of the multiple users, generating and/or storing respective visual content representing that user's physical reaction; (iii) generating a visual content composition that includes at least the generated and/or stored visual content for each of the multiple users; and (iv) outputting for presentation, the generated visual content composition.