User-Aware Content Capture With Cross-Device Response Augmentation
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Solution Overview
Problem
Existing media consumption devices lack user awareness for content capture, failing to automatically identify and record content relevant to a user's interests, and do not effectively integrate user activities or inputs from other devices with the content being played.
Innovation Solution
Implementing a user-aware automated content capture system that utilizes a content capture analyzer to predict user preferences and trigger content capture based on user actions, activities, and inputs from linked devices, and augments the captured content with user-generated information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated content capture is implemented without user awareness, then content capture automation is improved, but content selection accuracy deteriorates
Solution Approach 1:
The system incorporates user feedback mechanisms where user actions, activities, and inputs are continuously monitored and fed back to the content capture analyzer. This feedback loop enables the system to learn from user behavior patterns and improve content selection accuracy while maintaining automation. The analyzer adjusts capture decisions based on real-time user responses, resolving the contradiction between automation extent and selection precision.
Solution Approach 2:
The content capture analyzer operates autonomously by self-monitoring user states and automatically making capture decisions without requiring manual user intervention. The system serves itself by using its own collected data about user behavior to improve its content selection algorithm, thereby achieving both high automation and accurate content selection simultaneously.
2Measurement precision
If manual configuration is required for content capture, then content selection accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The system performs content capture configuration automatically by monitoring user behavior patterns without requiring manual user setup. The content capture analyzer self-determines capture parameters based on observed user activities, eliminating the need for manual configuration while maintaining accurate content selection through learned user preferences.
Solution Approach 2:
The system performs preliminary analysis of user behavior patterns and pre-configures content capture settings before actual content capture is needed. By anticipating user interests based on historical data and current activity context, the system prepares capture parameters in advance, making the operation effortless for users while ensuring accurate content selection.
3Measurement precision
If user awareness is added to content capture, then content selection accuracy is improved, but device complexity increases
Solution Approach 1:
The content capture analyzer is designed as a multi-functional component that simultaneously performs user state monitoring, behavior pattern recognition, content analysis, and capture decision-making. By consolidating multiple functions into a single universal analyzer, the system achieves high content selection accuracy without proportionally increasing overall device complexity.
Solution Approach 2:
The system merges the content capture analyzer with user activity monitoring and device input tracking into an integrated architecture. By combining previously separate functions (content analysis, user monitoring, and capture control) into a unified system, the patent reduces the cumulative complexity that would arise from adding independent modules for each function.
4Measurement precision
If multiple devices are integrated for user input collection, then content selection accuracy is improved, but device complexity increases
Solution Approach 1:
The content capture analyzer is designed as a universal interface that can collect and process inputs from multiple device types (smartwatches, tablets, cameras, microphones) through standardized protocols. This multi-functional design allows the system to integrate diverse devices without creating separate complex integration pathways for each device type, maintaining manageable system complexity while improving content selection accuracy through diverse data sources.
Data Source
AI summary
A method performed by a first electronic device includes receiving from a second electronic device an indication of an occurrence of one or more trigger conditions for content capture of multimedia content displayed on the first device, starting capture of the multimedia content in response to the trigger condition indication, collecting information from a third device, wherein the information from the third device is response information that is related to the multimedia content displayed on the first device, augmenting the captured multimedia content with the collected information from the third device for simultaneous display, and displaying the augmented multimedia content.