Adaptive HTTP Video Editing for Defect Segment Correction
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Solution Overview
Problem
Existing video editing technologies are inefficient in adapting to the live streaming environment, particularly in addressing defects in online video content that vary with networking, hardware, and software conditions, leading to interference with seamless content delivery.
Innovation Solution
A system for online video editing that includes detecting defects in the original video stream, creating a compact editable copy with marked editing positions, and constructing an edited video by replacing abbreviated summaries with corresponding segments, utilizing a navigable editing manifest to facilitate efficient editing across variant streams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If video editing is performed on original streaming video segments, then editing capability is provided, but streaming quality and seamless content delivery are degraded
Solution Approach 1:
The video stream is divided into multiple segments, with only defective segments extracted for editing while pristine segments are preserved in their original form. This segmentation allows editing operations to be performed on specific problematic portions without affecting the overall stream quality.
Solution Approach 2:
Defective video segments are extracted from the original stream for editing, while pristine segments are taken out and preserved separately. This extraction approach enables selective editing of only the problematic portions, maintaining the integrity of high-quality segments.
2Manufacturing precision
If complete video segments are edited, then editing precision is improved, but editing time and processing efficiency increase
Solution Approach 1:
Instead of editing complete video segments, the system performs partial editing by targeting only the specific defective portions within segments. This partial action approach maintains sufficient editing precision for correcting issues while dramatically reducing the amount of data that needs to be processed.
Solution Approach 2:
The editing process is segmented to work with individual defective portions rather than complete segments. This segmentation of the editing task itself allows precise correction of specific issues without the overhead of processing entire video segments.
3Measurement precision
If video defects are detected under all networking and hardware conditions, then detection accuracy is improved, but system complexity and processing overhead increase
Solution Approach 1:
The system performs defect detection selectively rather than universally across all conditions. By detecting defects under representative conditions and using adaptive streaming to deliver appropriate quality levels, the system achieves sufficient detection accuracy without the excessive complexity of testing all possible networking and hardware configurations.
Data Source
AI summary
Editing a video stream includes detecting defects in an original version of the video stream, marking up the original version of the video stream to indicate one or more segments having at least one of the defects that are detected, and building a compact editable copy of the original version of the video stream that includes editing positions corresponding to the one or more segments and includes abbreviated summaries of other segments of the original video stream that are between the editing positions. Editing a video stream also includes modifying the compact editable copy by editing the one or more segments having at least one of the defects to provide a modified compact editable copy and constructing an edited video by replacing the abbreviated summaries in the modified compact editable copy with corresponding ones of the other segments of the original video stream that are between the editing positions.