Facial Expression Correlation with Content Metadata
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Solution Overview
Problem
Content providers face challenges in effectively determining viewer reactions and preferences to their content, as traditional metrics like Nielsen ratings are limited in providing real-time and nuanced feedback.
Innovation Solution
A system that includes a processor and camera-enabled devices to capture viewer facial expressions during content consumption, using facial recognition software to generate signals representative of these expressions, which are then associated with metadata identifying the content, allowing for the creation of databases that track viewer opinions and emotions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional metrics like Nielsen ratings are used to gauge viewer popularity, then content providers can obtain basic viewing data, but the feedback is limited in providing real-time and nuanced viewer reactions
Solution Approach 1:
The patent replaces traditional mechanical rating systems with an automated facial recognition system using cameras and image processing algorithms. The system captures facial expressions in real-time during content viewing and automatically analyzes them to determine viewer reactions, eliminating the need for manual rating processes and providing immediate feedback.
Solution Approach 2:
The system enables viewers to implicitly provide feedback through their natural facial expressions while watching content. The automated recognition system interprets these expressions without requiring viewers to actively participate in rating processes, thus providing real-time feedback while viewers are naturally engaged with the content.
2Loss of information
If facial recognition technology is integrated with cameras and display devices, then content providers can obtain detailed viewer expression data, but the system complexity increases
Solution Approach 1:
The patent integrates the facial recognition system with existing camera and display devices that content providers already possess. The same camera infrastructure used for other purposes is leveraged to capture facial expressions, and the display devices serve both content presentation and potential feedback display functions, reducing the need for separate dedicated hardware.
Solution Approach 2:
The system introduces an intermediary processing layer that bridges the camera and content analysis functions. This intermediary module handles image capture, facial feature extraction, expression recognition, and data correlation with content metadata, simplifying the overall architecture by centralizing the complex processing tasks in a dedicated service layer.
3Productivity
If the system processes and stores detailed viewer expression data in databases, then content providers can analyze viewer preferences, but the data management complexity increases
Solution Approach 1:
The patent segments the data management process into distinct functional components: facial expression data capture, content metadata identification, opinion derivation from expressions, and structured storage in databases. This segmentation allows each component to be optimized independently and simplifies the overall data management architecture by dividing complex tasks into manageable modules.
Data Source
AI summary
A computer includes at least one processor and at least one computer readable storage medium accessible to the processor. The medium bears instructions executable by the processor to cause the processor to receive at least one image of at least one viewer of a display on which content is presented. The instructions also cause the processor to generate a signal representative of at least one expression of the viewer made at or around the time the content was presented based on the image of the viewer, and also to receive metadata identifying the content. The instructions then cause the processor to associate the metadata identifying the content with the at least one expression of the viewer.