Live Video Chaptering via Streamer Reaction Detection
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Solution Overview
Problem
Existing video distribution systems do not utilize the reaction of a streamer to posted comments, missing an opportunity to enhance viewer engagement and system usage.
Innovation Solution
A server device and method that distribute live videos to terminals with comment areas, receive and display comments, identify comments reacted to by the streamer, and set chapters in the live video based on the relative time of the streamer's reaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the distribution system displays comments and allows viewer interaction, then viewer engagement increases, but the streamer's reactions to comments are not utilized, missing an opportunity to enhance system usage
Solution Approach 1:
The system establishes a feedback loop where streamer reactions to comments are detected, processed, and converted into actionable chapter markers. The server monitors streamer input devices, identifies reaction patterns, and automatically creates chapter divisions based on these reactions, transforming passive streamer behavior into active system enhancement.
Solution Approach 2:
The system enables automatic chapter setting without requiring manual intervention from the streamer or post-processing. The streamer's natural reactions to comments automatically trigger chapter creation, allowing the system to self-enhance its functionality by utilizing the streamer's organic engagement patterns.
2Manufacturing precision
If chapters are set manually in live videos, then video segmentation is achieved, but it requires additional time and effort from the streamer
Solution Approach 1:
The system performs automatic chapter setting by detecting streamer reactions to comments and automatically creating chapter markers at the appropriate video timestamps. This eliminates the need for manual chapter creation, saving the streamer's time while maintaining precise video segmentation based on actual engagement moments.
Solution Approach 2:
The system proactively monitors streamer reactions in real-time and automatically creates chapter markers as they occur during the live stream, rather than requiring post-processing. This preliminary action ensures chapters are already established when needed, eliminating delays.
3Loss of information
If the system processes and displays all comments, then complete viewer feedback is captured, but the comment area becomes cluttered and harder to view
Solution Approach 1:
The system applies different display qualities to different comments based on their significance. Comments that trigger streamer reactions are highlighted or given special formatting, while other comments maintain standard display. This local differentiation maintains viewability by emphasizing important interactions without hiding other feedback.
Solution Approach 2:
The system uses visual differentiation such as color changes or special formatting for comments that receive streamer reactions. This allows viewers to quickly identify which comments are most engaging while still displaying all comments in the comment area, maintaining both completeness and ease of scanning.
Data Source
AI summary
A distribution controller (141) distributes a live video provided from a streamer to a plurality of terminals each of which has a comment area, the comment area allowing a predetermined number of comments to be displayed. A receiver (120) receives a comment posted from, among the plurality of terminals, a viewer terminal used by a viewer during distribution of the live video. A sender (110) sends a comment that the receiver (120) received to the plurality of terminals to cause the comment to be added to the comment areas in a last-in-first-out manner. An identifier (144) identifies, among respective comments currently being displayed in the comment area, a comment to which the streamer reacted. A setter (541) sets a chapter to divide the live video, based on a relative time in the live video corresponding to a time at which the identified comment is received.