Distance-Based Framing for Online Conference Video Stability
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Solution Overview
Problem
Conventional online conference systems often experience errors in video framing due to discrepancies between video and audio analysis, leading to unnecessary framing switches and reduced accuracy, as they rely solely on these analyses without confirmation from distance sensor data.
Innovation Solution
The implementation of distance-based framing techniques that utilize distance sensor data, such as radar data, to confirm or deny potential errors in current framings, ensuring accurate and stable video framing during online conferences by analyzing video, audio, and distance sensor data to determine the correct speaker location and movement within the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video and audio analysis are used to determine speaker location and generate framings, then framing composition is achieved, but framing errors occur due to discrepancies between video and audio analysis
Solution Approach 1:
The system uses distance sensor data as feedback to verify and correct framing decisions made through video and audio analysis. When discrepancies are detected between multiple data sources, the distance sensor information provides corrective feedback to generate accurate framings, resolving the contradiction between framing composition and framing accuracy.
Solution Approach 2:
Distance sensor data acts as an intermediary verification layer between video and audio analysis. This intermediary data source cross-validates the results from video and audio streams, eliminating framing errors caused by discrepancies in the original analysis methods.
2Measurement precision
If framing switches are performed frequently to correct detected errors, then framing accuracy is improved, but unnecessary framing switches occur reducing system stability
Solution Approach 1:
The system performs preliminary verification of framing decisions using distance sensor data before executing framing switches. This preliminary action filters out false positives from video and audio analysis, ensuring that only necessary and accurate framing changes are implemented, thereby maintaining stability while improving accuracy.
3Measurement precision
If multiple data sources (video, audio, distance sensor) are analyzed to confirm framing accuracy, then framing precision is improved, but processing complexity increases
Solution Approach 1:
The system applies partial action by using distance sensor data selectively only when discrepancies are detected in video or audio analysis, rather than continuously processing all data sources simultaneously. This approach improves framing precision when needed while minimizing unnecessary processing complexity during normal operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces unnecessary framing switches and improves the accuracy of video framing, enhancing the online conference experience by ensuring that the video stream is reframed only when necessary, thereby minimizing processing operations and maintaining a stable meeting environment.
Implementation Method 1
distance sensor data, such as radar data
Data Source
AI summary
Distance-based framing includes obtaining at least a video stream during an online conference session. The video stream, an audio stream received with the video stream, or both the video stream and the audio stream are analyzed and a framing that either focuses on a speaker in the video stream or provides an overview of participants in the video stream, the framing being is composed based on the analyzing. A potential error in the framing is detected based on further analysis of the video stream, the audio stream, and an amount of motion in the room. If the distance sensor data contradicts the potential error, the framing is maintained, but if the distance sensor data confirms the potential error, a new framing is generated.