Adaptive Video Encoding Using User Reaction Feedback
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Solution Overview
Problem
Existing video communication systems face challenges in accurately reflecting user experience due to reliance on objective measures, which can lead to suboptimal video quality adjustments and increased network traffic when addressing packet loss or network congestion, as they fail to incorporate real-time subjective user feedback effectively.
Innovation Solution
The system collects and analyzes naturalistic video data by transmitting video streams between users, determining user reactions to video quality fluctuations, and using these reactions to adjust encoding parameters in real-time, thereby optimizing video viewing experiences based on subjective user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If objective measure-based methods (PSNR, SSIM) are used to evaluate and control video quality, then video quality can be evaluated and controlled, but user experience cannot be accurately reflected because objective measures fail to incorporate real-time subjective user feedback
Solution Approach 1:
The system introduces feedback loops where user reactions to video quality are captured, processed into tags, and used to adjust encoding parameters in real-time. This creates a closed-loop system that continuously incorporates subjective user feedback to improve video quality evaluation and control.
Solution Approach 2:
The patent introduces an intermediary processing layer that converts subjective user reactions into objective tags that can be used by the encoding system. This intermediary layer bridges the gap between subjective user experience and objective quality metrics.
2Productivity
If encoding parameters are adjusted based on network conditions alone, then bandwidth efficiency can be improved, but video quality optimization is suboptimal because user perceptions are not considered
Solution Approach 1:
The system dynamically adjusts encoding parameters based on real-time user reactions rather than static network conditions alone. The encoding process becomes adaptive and responsive to changing user needs and perceptions throughout the video transmission.
Solution Approach 2:
The patent changes the parameters used for encoding decisions from purely network-based metrics to include user reaction tags. This allows the system to optimize video quality according to actual user perceptions while maintaining bandwidth efficiency.
3Reliability
If more video data is transmitted to maintain quality during packet loss or network congestion, then video quality can be preserved, but network traffic increases which can worsen congestion
Solution Approach 1:
Instead of uniformly increasing video data transmission, the system applies partial action by selectively adjusting encoding parameters only for areas of interest identified through user reactions. This allows quality preservation in critical regions while reducing overall network traffic.
Data Source
AI summary
Techniques for video communications include: transmitting, from a first apparatus, a first video stream of a first user to a second apparatus of a second user; receiving, from the second apparatus, a second video stream of the second user; determining a reaction of the second user to an area of interest in the first video stream using the second video stream; and updating a parameter for encoding the area of interest in the first video stream based on the reaction of the second user to the area of interest in the first video stream, and one or more tags associated with the reaction of the second user are used to train an adaptive encoder to automatically adjust the parameter for encoding the area of interest in the first video stream to optimize video viewing experiences based on the reaction of the second user.