Gesture-Based Content Feedback for Cross-Platform Personalization
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Solution Overview
Problem
Current content delivery systems are cumbersome and inefficient in capturing user feedback through traditional input methods, such as remote controls, which discourage users from providing feedback regularly and delay content generation, especially when switching between different platforms.
Innovation Solution
A system that captures user gestures, including biometric data like hand movements and facial expressions, to generate a personalized content list, allowing seamless feedback capture and quick content launch across platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional input methods (remote control, mobile phone) are used to capture user feedback, then feedback can be recorded, but the process becomes cumbersome and discourages regular user participation
Solution Approach 1:
The patent replaces mechanical input methods (remote control buttons, mobile phone interfaces) with gesture recognition technology. The system captures hand gestures through cameras or sensors and translates them into feedback signals, eliminating the need for physical button pressing or complex interface navigation. This substitution maintains feedback accuracy while dramatically improving ease of operation.
Solution Approach 2:
The system enables users to provide feedback naturally through their own gestures without requiring them to learn or adapt to specific input device operations. The gesture recognition system interprets natural hand movements as feedback indicators, allowing users to interact with the content delivery system using their own body language rather than being constrained by device-specific controls.
2Reliability
If multiple steps are required to provide feedback through traditional interfaces, then feedback can be captured, but hardware execution is slowed and user experience is degraded
Solution Approach 1:
By replacing multi-step mechanical input sequences with single-gesture recognition, the system eliminates intermediate steps in the feedback capture process. The gesture recognition system processes hand movements directly into feedback signals without requiring users to navigate through menus, select options, or confirm inputs, thereby maintaining accuracy while dramatically increasing capture speed.
Solution Approach 2:
The system performs preliminary gesture recognition and interpretation in real-time as the user makes the gesture, rather than waiting for complete input sequences. This allows the system to anticipate and process feedback intent before the user completes the full gesture motion, reducing overall processing time while maintaining accurate feedback capture.
3Reliability
If users must manually switch platforms to provide feedback on advertised content, then feedback can be captured, but the process becomes tedious and delays content generation
Solution Approach 1:
The gesture recognition system provides a universal feedback mechanism that works across multiple platforms and content sources without requiring users to switch devices or applications. Whether the user is viewing content on a TV, computer, or mobile device, the same gesture-based interface can be used to provide feedback on any advertised content, eliminating platform-specific barriers and reducing time loss.
Solution Approach 2:
The system introduces a gesture recognition intermediary that bridges the gap between users and content across different platforms. Instead of requiring direct interaction with each platform's native interface, the gesture system serves as a universal mediator that translates physical gestures into platform-agnostic feedback signals, enabling seamless cross-platform feedback capture without manual switching.
4Reliability
If traditional feedback methods are used, then user input can be recorded, but the complexity of input steps increases and user engagement decreases
Solution Approach 1:
The patent replaces complex mechanical input systems (remote controls, keyboard interfaces, touchscreen navigation) with gesture recognition technology. This substitution simplifies the input process by eliminating the need for users to learn and operate complex device interfaces, while maintaining reliable feedback data capture through accurate gesture interpretation and classification.
Data Source
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AI summary
Systems and methods are presented for providing personalized content based on gestures, in order to provide a seamless and user-driven feedback capture platform that captures user gestures and provides improved personalized content. The system captures biometric data from the user during the presentation of a first content item from a first content source. The system identifies the feedback indicator from the biometric data captured during the output of the first content item and stores an identifier of the second content item associated with the first content item in the master list. The system generates the master list for display and, in response to receiving a selection of the identifier of the second content item, retrieves for output the second content item from the second content source on the user device.