Context-Triggered Freeze-Frame Video for Unstable Live Feeds
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Solution Overview
Problem
Video communication sessions often experience issues with frozen or low-quality live video feeds, and participants may inadvertently leave their local video feed on, distracting others and degrading the experience.
Innovation Solution
An electronic device equipped with AI-driven freeze frame video functionality that generates and presents freeze frame videos in response to context-based triggers, such as loss of signal, low quality, or specific participant actions, allowing participants to temporarily pause their live feed without fully disconnecting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the local video feed is kept on during a video communication session, then the participant remains visible and engaged to other users, but the video quality may degrade or freeze, and the participant's distracted state may be inadvertently revealed
Solution Approach 1:
The system proactively detects trigger conditions (such as video quality degradation, freezing, or participant distraction) and automatically switches to a pre-prepared freeze frame image before the video feed completely fails or reveals the participant's distracted state. This preliminary action maintains video reliability and quality consistency by having a backup visual state ready in advance.
2Ease of operation
If the participant turns off the local video feed to avoid showing their distracted state, then professionalism is maintained, but the participant becomes invisible to other users
Solution Approach 1:
The system creates a static copy (freeze frame image) of the participant's video feed and uses this copy as a replacement when the live video becomes problematic. This copying approach allows the participant to remain visually present in the communication session while avoiding exposure of their distracted state, maintaining both visibility and professionalism.
3Reliability
If the system automatically detects and responds to video feed issues, then video quality and engagement are maintained, but the system complexity increases
Solution Approach 1:
The system implements feedback mechanisms by monitoring video feed quality metrics and participant behavior patterns, then automatically adjusting the video output based on detected conditions. This feedback loop maintains video communication quality through automated detection and response to issues such as freezing, low quality, or participant distraction, without requiring manual intervention.
Data Source
AI summary
An electronic device, a method, and a computer program product provides freeze frame videos in place of a live video feed or a low-quality video feed to a video communication session. The electronic device hosts the video communication session between a first participant device and second participant devices. The electronic device receives, from the first participant device, a first video feed of a first participant to the video communication session. The electronic device determines a video segment of the received first video feed to identify as the first freeze frame video, generates the first freeze frame video from the video segment, and stores the first freeze frame video within a server repository. In response to a trigger condition, the electronic device temporarily presents to the video communication session the first freeze frame video in place of the first video feed as video content from the first participant device.