Media Content Summary Based on Viewer Annotations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing media content summaries are often created by experts and may not accurately reflect viewer interest, limiting users' ability to efficiently find engaging segments of media content without watching the entire content.
Innovation Solution
A system that utilizes viewer annotation data to generate a media content summary by identifying and selecting segments based on user-specified criteria, using a media content analyzer that aggregates and analyzes viewer responses, such as facial expressions, text inputs, and emoticon selections, to create a summary that includes only the most interesting portions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expert-created media summaries are used, then professional quality and curation are improved, but viewer interest accuracy and personalization deteriorate
Solution Approach 1:
The system collects viewer annotations (facial expressions, text inputs, emoticon selections) as feedback during media consumption and uses this feedback to dynamically adjust and personalize media summaries, transforming static expert-created content into adaptive, viewer-specific recommendations
Solution Approach 2:
The media summary system transitions from static expert-curated content to dynamic, real-time personalized summaries that adapt based on individual viewer responses and preferences, allowing the summary to evolve as viewer interest is measured and understood
2Loss of information
If complete media content is viewed, then comprehensive understanding is improved, but time consumption deteriorates
Solution Approach 1:
The system extracts and presents only the most relevant and interesting segments of media content based on measured viewer interest, removing unnecessary portions while retaining essential information, thereby reducing viewing time without sacrificing comprehensive understanding
Solution Approach 2:
Instead of requiring complete media consumption, the system provides a partial viewing experience through personalized summaries that contain sufficient information for decision-making, allowing viewers to obtain adequate understanding with less than full content exposure
3Ease of operation
If traditional media summaries are used, then ease of browsing is improved, but accuracy in reflecting viewer interest deteriorates
Solution Approach 1:
The system enables viewers to automatically generate personalized media summaries through self-service mechanisms where individual viewer annotations and responses are automatically collected, analyzed, and used to create customized content recommendations without requiring manual curation
Data Source
AI summary
A method includes receiving, at a media server, a request to create a media content summary. The request includes a user-specified criterion. The method includes identifying segments of media content based on annotation data. The annotation data includes annotations associated with a first segment of the segments and a second segment of the segments. The first segment is identified based on a number of corresponding annotations. The method further includes generating the media content summary by automatically changing a first size of the first segment and a second size of the second segment such that a total size of the media content summary satisfies the user-specified criterion.