Dynamic Spatial Resolution Video Transcoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video transcoding methods fail to dynamically adjust video stream resolution in response to changing network conditions, leading to suboptimal video quality and increased latency or glitching during playback.
Innovation Solution
A method and apparatus for transcoding a compressed video stream by decoding it, dynamically modifying its spatial resolution based on current bitrate, quantization parameters, spatial complexity, and temporal complexity, and re-encoding it for transmission over a network, allowing for real-time adaptation to maximize video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multi bit rate coding is used to encode video at different coding rates, then video quality can be optimized according to network conditions, but the device complexity and processing overhead increase
Solution Approach 1:
The patent applies dynamics by making the spatial resolution modifiable during transcoding based on real-time network conditions. Instead of pre-encoding multiple versions, the system dynamically adjusts resolution parameters during the transcoding process, allowing adaptive optimization without requiring multiple static encodings. This resolves the contradiction by providing video quality optimization through dynamic parameter adjustment rather than static multi-version encoding.
Solution Approach 2:
The patent changes the spatial resolution parameter dynamically during transcoding based on network conditions, quantization parameters, and video complexity metrics. By modifying resolution as a variable parameter rather than a fixed property, the system achieves quality optimization without the complexity of maintaining multiple encoded versions. This directly addresses the contradiction by using parameter flexibility to replace structural complexity.
2Adaptability or versatility
If real-time transcoding is performed to transform video from one compressed format to another, then adaptability to different client devices is improved, but processing time and latency increase
Solution Approach 1:
The patent applies partial action by selectively modifying only the spatial resolution parameter during transcoding rather than performing complete re-encoding. The system adjusts resolution based on specific conditions (network state, video complexity, quantization parameters) while maintaining other encoding characteristics. This partial modification approach provides client adaptability while significantly reducing processing time compared to full transcoding operations.
Solution Approach 2:
The system performs preliminary analysis of network conditions, video complexity, and quantization parameters before executing resolution modification. By pre-assessing these factors, the transcoding process can be optimized in advance, reducing actual processing latency. The preliminary evaluation allows the system to prepare appropriate resolution adjustments without requiring extensive real-time computation during playback.
3Manufacturing precision
If higher bit rate is specified for encoding video, then video quality and accuracy are improved, but network transmission efficiency decreases
Solution Approach 1:
The patent dynamically adjusts spatial resolution during transcoding based on real-time network conditions, allowing the system to optimize the balance between video accuracy and transmission efficiency. When network conditions are good, higher resolution is maintained for better quality; when conditions deteriorate, resolution is reduced to improve transmission efficiency. This dynamic adaptation resolves the contradiction by making video accuracy flexible rather than fixed.
Solution Approach 2:
The system changes the spatial resolution parameter in response to network conditions, quantization parameters, and video complexity metrics. By making resolution a variable parameter that adapts to current conditions, the system achieves optimal video accuracy while maintaining network transmission efficiency. This parameter flexibility allows the system to avoid the trade-off between fixed high accuracy and transmission efficiency.
4Manufacturing precision
If spatial resolution is dynamically modified during transcoding, then video quality is optimized for varying network conditions, but processing complexity increases
Solution Approach 1:
The patent modifies spatial resolution as a key parameter during transcoding based on network conditions, quantization parameters, and video complexity. By focusing changes on this single critical parameter rather than comprehensive re-encoding, the system achieves video quality optimization with controlled processing complexity. The parameter change approach maintains simplicity while delivering adaptive quality.
Solution Approach 2:
The system uses feedback from network conditions, quantization parameters, and video complexity metrics to guide resolution modification decisions. This feedback mechanism allows the transcoding process to adapt intelligently without requiring complex pre-computation or exhaustive analysis. The feedback-driven approach optimizes video quality while keeping processing complexity manageable through condition-based decision making.
Data Source
AI summary
An apparatus and method are disclosed for transcoding a compressed video stream. In one embodiment, a compressed video stream is decoded. A spatial resolution of the decoded video stream can then be dynamically modified. The video stream with the modified spatial resolution can be re-encoded and transmitted over a network for display on a client device. The spatial resolution can be dynamically modified based on a variety of techniques. For example, a current bitrate and quantization parameters associated with the frames can be used to determine the spatial resolution. Alternatively, the spatial and/or temporal complexity can be used to modify spatial resolution.