Video Call Gesture Evaluation and Reputation Quotient System
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Solution Overview
Problem
Current video call services lack a mechanism to evaluate user interactions and provide personalized feedback based on gestures, which can lead to unengaging or mismatched user interactions.
Innovation Solution
A terminal and server system that detects user gestures during video calls, generates evaluation information, and updates a reputation quotient for users, allowing for improved matching and interaction management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video call services connect users randomly without evaluation mechanisms, then service simplicity is maintained, but user engagement and interaction quality deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where user gestures during video calls are detected, evaluated, and converted into evaluation information that is stored and used to generate personalized feedback. The server receives video streams, detects gestures using image processing, generates evaluation scores, and provides feedback to users, creating a closed-loop system that continuously improves interaction quality based on observed user behavior.
Solution Approach 2:
The patent introduces an intermediary evaluation system that mediates between raw user gestures and personalized feedback. The server acts as an intermediary that receives video streams from terminals, processes gestures through image recognition algorithms, generates evaluation information, and transmits feedback to users, thereby bridging the gap between simple video calling and complex personalized interaction management.
2Productivity
If gesture detection and evaluation is implemented, then user engagement improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by selectively detecting only relevant gestures that indicate meaningful user feedback rather than processing all video data continuously. The system identifies specific gesture patterns (such as thumbs up, thumbs down, or other expressive movements) and processes only those frames containing detectable gestures, reducing overall computational load while maintaining effective user engagement monitoring.
3Measurement precision
If evaluation information is collected and stored for all users, then personalized matching improves, but data storage requirements increase
Solution Approach 1:
The patent extracts only the essential evaluation information from video streams rather than storing complete video data or all processed frames. The system detects gestures, converts them into discrete evaluation scores or categories (such as positive/negative feedback, engagement level), and stores only these extracted evaluation metrics in the server database, significantly reducing storage requirements while maintaining accurate user behavior analysis capability.
Data Source
AI summary
Provided are a terminal for providing a video call service by generating evaluation information corresponding to a gesture of a user of a video call service and a server for providing a video call service based on a reputation quotient of a user based on the evaluation information received from the terminal.