Parallel Video Encoding via Complexity-Based Bandwidth Allocation
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Solution Overview
Problem
Existing video encoding methods that encode different portions of a video file in parallel often result in lower quality encodings since individual encoders cannot account for the complexity of the source video as a whole, leading to inefficient allocation of encoding bandwidth and delayed content release.
Innovation Solution
A method that generates complexity data for a source video file, divides it into chunks based on relative complexity, and allocates encoding bandwidth accordingly, allowing each chunk to be encoded at a rate that reflects its complexity relative to other chunks, enabling higher-quality encoding by accounting for complexities across the entire video.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video encoding is performed in parallel on multiple portions separately, then encoding speed and productivity are improved, but encoding quality deteriorates because individual encoders cannot account for overall video complexity
Solution Approach 1:
The video is divided into multiple portions that can be encoded in parallel, improving productivity. However, a central controller coordinates these segments by analyzing overall complexity to allocate bandwidth appropriately, ensuring quality is maintained despite segmentation.
Solution Approach 2:
A central controller receives complexity information from all video portions, analyzes the overall video complexity, and provides feedback in the form of bandwidth allocation decisions to each encoder. This feedback loop ensures that individual encoders can produce high-quality output by understanding their portion's complexity relative to the whole video.
2Device complexity
If equal encoding bandwidth is allocated to all video portions, then encoding process is simplified, but encoding quality deteriorates because complexity variations across different portions are not accounted for
Solution Approach 1:
Instead of applying uniform encoding bandwidth across all video portions, the system allocates bandwidth locally to each portion based on its specific complexity characteristics. The central controller analyzes complexity metrics for each portion and distributes encoding resources accordingly, ensuring that complex portions receive more bandwidth while simpler portions receive less, thereby optimizing overall encoding quality.
3Productivity
If complexity analysis is performed only within individual video portions during parallel encoding, then encoding speed is maintained, but encoding quality deteriorates because the most complex frames may be relatively simple in the context of the entire source video
Solution Approach 1:
The system merges the complexity analysis function into a central controller that processes information from all video portions simultaneously. This centralization allows the system to maintain parallel encoding speed while achieving accurate overall complexity assessment, as the controller can compare complexity metrics across all portions and make informed bandwidth allocation decisions based on the complete picture.
Data Source
AI summary
Embodiments of the invention provide techniques for encoding chunks of a video file in parallel. Embodiments may divide a source video file into a plurality of chunks, and may encode each chunk at a rate based upon complexity data associated with the chunk. The encoded chunks may then be reassembled to produce an encoded video file.