Video Transcoder Using Hint Signals for Complexity Control
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Solution Overview
Problem
Current video transcoding methods, such as Full Transcoding and SHVC, face challenges in balancing storage gains and transcoding complexity while maintaining high intrinsic visual quality, with existing techniques either requiring high processing costs or inducing bitrate overheads and limited adoption due to complexity.
Innovation Solution
A method and transcoder that utilize transcoding hint signals to adapt prediction search techniques and associated complexity costs, allowing for controlled transcoding complexity and reduced storage needs by generating a Transcoding Hint Signal (THS) that contains reduced information, enabling efficient transcoding of video streams from a reference quality to other qualities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If Full Transcoding is used to store only highest quality and transcode lower qualities on demand, then storage gains are very high, but processing cost of transcoding is very high
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing motion search results and prediction data during the encoding of the reference quality video stream. These pre-computed data are stored as side information that can be directly reused during transcoding operations, eliminating the need to perform full motion searches again when transcoding to different qualities. This significantly reduces the processing cost of on-demand transcoding while maintaining high storage gains.
Solution Approach 2:
The patent uses copying by directly reusing motion vectors, prediction data, and other encoding parameters from the reference quality stream during transcoding. Instead of recomputing these parameters from scratch, the transcoder copies and adapts them for the target quality, dramatically reducing the computational complexity of transcoding while preserving video quality.
2Productivity
If transcoding complexity is reduced by limiting search ranges, then processing cost decreases, but video output quality is not guaranteed
Solution Approach 1:
The patent implements feedback by using the pre-computed motion search results and prediction data from the reference quality encoding as guidance during transcoding. The transcoder evaluates the quality impact of using these pre-computed parameters and adapts the transcoding process accordingly, ensuring that video output quality is maintained while benefiting from reduced processing complexity. The side information acts as feedback that guides the transcoding to achieve optimal quality-efficiency tradeoff.
Solution Approach 2:
The patent applies parameter changes by adapting the pre-computed motion vectors and prediction parameters from the reference quality to the target quality through scaling and adjustment operations. Rather than using fixed search ranges that may compromise quality, the system dynamically adjusts parameters based on the relationship between reference and target qualities, ensuring both speed and quality requirements are met.
3Quantity of substance
If lower-quality streams are purged to save storage space, then storage requirements decrease, but transcoding operation becomes costly when content is requested
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing essential encoding parameters and motion data during the initial encoding of the reference quality stream. This side information is stored in a compact form that requires minimal additional storage space. When transcoding is needed, this pre-computed data is reused, dramatically reducing the energy cost of transcoding purged content while maintaining acceptable video quality.
4Productivity
If Control Streams are used to reduce transcoding complexity, then processing cost decreases, but Transcoding Hint Signals are significantly larger reducing storage gains
Solution Approach 1:
The patent applies the taking out principle by extracting only the essential and most impactful encoding parameters from the reference quality stream for use in transcoding. Instead of storing complete Control Streams with all possible data, the system selectively extracts motion vectors, prediction modes, and other critical parameters that provide the greatest benefit for transcoding efficiency. This selective extraction significantly reduces the size of the side information while maintaining high transcoding performance.
Data Source
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AI summary
A method for transcoding a video stream encoded in a reference quality into at least one other quality, the method comprising: receiving the video stream in the reference quality; receiving at least one transcoding hint signal comprising: at least one transcoding instruction hint for adapting a prediction search technique for encoding the video stream into the at least one other quality; and at least one respectively associated complexity cost of performing the respective adapted prediction search technique; the transcoding hint signals corresponding respectively with the other qualities; extracting from the at least one transcoding hint signal the at least one transcoding instruction hint and the at least one respectively associated complexity cost; decoding the received video stream; and encoding the decoded video stream in the at least one other quality, taking into account the extracted at least one transcoding instruction hint and the at least one associated complexity cost.