Video Stream Stabilization for Online Meeting Participant Orientation
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Solution Overview
Problem
During video conferencing, participants' movements often cause their orientation to change within the video stream, leading to partial or complete exclusion from the view, diminishing the user experience for others.
Innovation Solution
A method and system that determine a reference image of a participant's orientation and adjust the video stream in real-time to stabilize their appearance, using a computing device to modify the video stream by comparing frames to the reference image and making necessary adjustments, such as resizing or repositioning the participant's face.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If participants are allowed to move freely during online meetings, then ease of operation is improved, but participant orientation stability deteriorates
Solution Approach 1:
The system continuously monitors participant orientation in the video stream and provides real-time feedback by comparing current frames against a reference image. When orientation changes are detected, the system automatically adjusts the video stream to maintain proper participant positioning, creating a closed-loop control system that stabilizes orientation while allowing natural movement.
2Reliability
If video stream processing is performed to stabilize participant orientation, then participant visibility is improved, but device complexity increases
Solution Approach 1:
The video processing system performs self-service by automatically detecting orientation changes, comparing them against the reference image, and adjusting the video stream without requiring external intervention. The system manages its own stabilization process through automated image analysis and transformation, reducing the need for complex manual configuration or additional hardware.
3Ease of operation
If real-time video stream modification is performed, then user experience is improved, but use of energy increases
Solution Approach 1:
The system applies partial action by only processing and modifying video frames when orientation changes are detected, rather than continuously processing every frame. This selective approach maintains user experience quality by stabilizing participant appearance only when necessary, thereby reducing overall energy consumption compared to continuous full-frame processing.
Data Source
AI summary
In one aspect, an example methodology implementing the disclosed techniques can include, by a first computing device, determining a reference image showing (e.g., encoding) an orientation of a user participating in an online meeting and receiving a video stream captured by a camera, the video stream associated with the online meeting. The method can also include, by the computing device, responsive to a determination of a change in the orientation of the user appearing within the video stream, providing modified video stream in which the orientation of the user is adjusted based on the reference image.