Rolling Buffer for Retroactive Audio-Video Clip Capture
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Solution Overview
Problem
Existing technologies fail to efficiently capture and edit audio-video clips during live sessions, requiring significant delays and lacking flexibility in managing multiple audio and video streams, especially when users want to retroactively capture or edit clips after an event.
Innovation Solution
The system employs a rolling buffer to store audio-video streams, allowing for immediate clip creation and editing, with independent management of multiple audio and video streams, optimized video encoding for client devices, and integration with machine learning for predicting user needs, enabling quick clip saving and editing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a rolling buffer is used to store audio-video streams for retroactive clip capture, then the speed of clip creation is improved, but the memory consumption increases
Solution Approach 1:
The system dynamically adjusts the rolling buffer size and video encoding parameters (resolution, bitrate, frame rate) to optimize the balance between clip creation speed and memory consumption. By changing these parameters based on available resources and user needs, the system can rapidly create clips while managing memory usage effectively.
Solution Approach 2:
Instead of storing all raw audio-video data indefinitely, the system creates compressed copies of the video streams in the rolling buffer. These compressed representations allow for rapid clip extraction and editing while significantly reducing the memory footprint compared to storing uncompressed original streams.
2Adaptability or versatility
If multiple audio and video streams are managed independently for flexible editing, then the adaptability is improved, but the device complexity increases
Solution Approach 1:
The system segments the audio-video streams into independent, manageable units that can be individually processed and edited. Each stream is handled as a separate entity with its own metadata, allowing flexible recombination and editing while using modular processing pipelines to manage the complexity of handling multiple streams simultaneously.
Solution Approach 2:
The system implements a universal stream processing framework that can handle multiple types of audio and video streams through common interfaces and processing routines. This multi-functional approach allows the same system architecture to manage diverse stream types without proportionally increasing complexity, as the processing logic is generalized and reusable across different stream configurations.
3Productivity
If optimized video encoding is applied for client devices, then the productivity is improved, but the manufacturing precision decreases
Solution Approach 1:
The system dynamically adjusts video encoding parameters such as resolution, bitrate, and compression level based on the target client device capabilities and the specific clip context. This allows rapid encoding for efficient clip creation and sharing while maintaining acceptable quality levels appropriate for each device type and use case.
Solution Approach 2:
The system applies different quality levels to different regions or portions of the video content based on importance. Critical moments or areas of interest are encoded with higher quality, while less important portions use lower quality settings, optimizing the balance between overall clip quality and encoding speed for rapid deployment.
Data Source
AI summary
The disclosed technology addresses the need in the art for to facilitate user accounts participating in live audio-video sessions such as voice and/or video calls, or watching game play remotely to capture a clip of the video call or game play after seeing some event during the live audio-video session. The present technology can maintain a rolling buffer of the audio-video streams such that a user account can retroactively capture a clip of the audio-video streams after it has already been presented.