Gaze-Responsive Content Distribution for Viewer Attention Guidance
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Solution Overview
Problem
There is a need to increase the appeal of content to viewers by considering their reactions to the content.
Innovation Solution
A content distribution system that analyzes line-of-sight data from multiple users to determine the distribution of viewer attention and applies audiovisual effects based on this distribution to enhance viewer engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is distributed to multiple user terminals without considering viewer reactions, then content distribution is simple and efficient, but the appeal and engagement of the content to viewers is limited
Solution Approach 1:
The system acquires line-of-sight data from multiple user terminals as feedback about viewer attention, analyzes this feedback to calculate attention distribution, and uses the analysis results to dynamically determine modes of applying effects to content. This closed-loop feedback mechanism enables the system to adapt content delivery to viewer reactions, resolving the contradiction between simple distribution and high appeal.
Solution Approach 2:
The system dynamically adjusts content delivery by determining different modes of applying effects based on real-time line-of-sight data analysis. Instead of static content distribution, the system adapts its behavior according to viewer attention patterns, making the content more appealing while managing complexity through automated dynamic decision-making.
2Measurement precision
If line-of-sight data is collected and analyzed from multiple users, then the system can determine content appeal based on viewer reactions, but the system complexity and data processing requirements increase
Solution Approach 1:
The system uses line-of-sight data as a proxy or copy of viewer reaction and attention patterns. Instead of directly measuring complex viewer responses, the system captures simplified line-of-sight position data that represents viewer engagement, processes this easier-to-obtain data, and infers viewer reactions from the line-of-sight distribution patterns.
Solution Approach 2:
The system transforms complex viewer reaction data into quantifiable parameters by calculating the distribution of line-of-sight positions. By converting qualitative viewer engagement into measurable spatial parameters (line-of-sight positions and their distributions), the system enables precise measurement of viewer reactions while managing data processing complexity through parameterization.
3Productivity
If effects are applied to content based on analyzed line-of-sight distribution, then viewer engagement is enhanced, but the complexity of content delivery increases
Solution Approach 1:
The system segments the content delivery process into distinct phases: acquiring line-of-sight data, analyzing the data to calculate distribution, determining appropriate effect modes, and applying effects to content. This segmentation allows complex viewer engagement enhancement to be broken down into manageable steps, improving productivity while controlling delivery complexity through systematic processing.
Solution Approach 2:
The system automatically determines the modes of applying effects based on the analyzed line-of-sight distribution without requiring manual intervention. The automated decision-making process uses the calculated attention distribution to select appropriate effects, enhancing viewer engagement while managing complexity through self-service automation rather than manual content delivery adjustments.
Data Source
AI summary
A content distribution system according to one embodiment includes at least one processor. The at least one processor is configured to display content on a plurality of user terminals, acquire line-of-sight data indicating line-of-sight positions of users visually recognizing the content from two or more of the plurality of user terminals, analyze two or more pieces of the acquired line-of-sight data to calculate a distribution of line-of-sight positions of two or more users in the content, and determine, based on the calculated distribution, a mode of applying an effect to be applied to the content displayed on at least one target terminal of the plurality of user terminals.