Automated Media Quality Analysis and Re-transcoding System
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Solution Overview
Problem
Video sharing websites face challenges in maintaining video quality due to issues like interlacing and video blocking, which degrade the viewing experience and are exacerbated by the need for transcoding millions of videos into various formats for different devices and services, making manual quality checking cumbersome.
Innovation Solution
A system comprising a media analysis unit, a media quality manager, and a re-transcode unit that detects phenomena such as interlacing and blocking, determines transcoding parameters, and re-transcodes videos to improve quality, using a centralized media organizer to store and recall parameters for efficient re-transcoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If videos are transcoded into numerous formats for different devices and services, then compatibility and adaptability are improved, but the complexity of managing video quality and detecting artifacts increases
Solution Approach 1:
The system segments the video processing workflow into distinct modular components: initial transcoding to multiple formats, separate quality analysis stage, and selective re-transcoding stage. This segmentation allows each component to be optimized independently, managing complexity while maintaining adaptability across multiple video formats and devices.
2Measurement precision
If manual quality checking is performed on uploaded videos, then detection precision is improved, but productivity and efficiency deteriorate
Solution Approach 1:
The system replaces manual mechanical quality checking with an automated digital analysis system that uses computational algorithms to detect interlacing artifacts and other video defects. This substitution maintains high detection precision while dramatically improving processing throughput and eliminating the bottleneck of manual review.
3Manufacturing precision
If re-transcoding is performed on all videos to improve quality, then manufacturing precision is improved, but loss of time and energy increase
Solution Approach 1:
The system applies local quality control by analyzing each video individually and applying re-transcoding only to specific videos that contain detected artifacts or quality issues. This selective approach maintains high video quality consistency where needed while avoiding unnecessary processing time and energy consumption for already-quality videos.
4Ease of manufacture
If interlacing artifacts are present in uploaded videos, then ease of manufacture is improved (simpler upload process), but object-affected harmful factors increase (degraded viewing experience)
Solution Approach 1:
The system performs preliminary quality analysis on uploaded videos to detect interlacing artifacts before the videos are distributed to users. By identifying problematic videos in advance, the system can apply corrective re-transcoding to remove artifacts, thereby eliminating harmful factors while maintaining the simplicity of the original upload process for users.
Data Source
AI summary
A system and method for managing media quality is provided. The system includes a data store with a computer readable medium storing a program of instructions for the managing of media quality; a processor that executes the program of instructions; a media analysis unit to receive transcoded media from a media store, and to detect for a phenomena affecting the transcoded media; a media quality manager, in response to the media analysis unit detection of the phenomena, determining a parameter for transcoding media; and a re-transcode unit to re-transcode the transcoded media based on the parameter.