Video Decoding with Key-Frame Prioritization for Speed and Accuracy
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Solution Overview
Problem
Existing video decoding methods fail to consider the concept of a group of pictures (GOP) and the importance of key frames, leading to slow decoding speed and missed frames, particularly those with significant picture changes.
Innovation Solution
A video decoding method that involves performing video stream analysis to determine frame types, selecting target sampling frames based on key frames, and storing rendering data in frame buffers to accelerate and improve decoding accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If all video frames are decoded using the same method, then decoding completeness is maintained, but decoding speed becomes slow
Solution Approach 1:
The patent segments video frames into different types (key frames and non-key frames) based on their importance and decoding requirements. Key frames are decoded completely while non-key frames use differential decoding, allowing selective processing that maintains completeness for important frames while speeding up processing for less critical frames.
Solution Approach 2:
Different decoding methods are applied to different frame types: key frames receive full decoding treatment while non-key frames receive differential decoding. This local differentiation in processing quality matches the actual importance of each frame type, improving overall decoding speed without sacrificing critical information.
2Reliability
If uniform frame capture algorithm is used for all frames, then processing simplicity is maintained, but key frames with significant picture changes may be missed
Solution Approach 1:
The patent performs preliminary analysis of frame attributes (such as picture change magnitude) before the main decoding process. This preliminary action identifies key frames that require special attention, ensuring they are not missed while allowing uniform processing for other frames, thus balancing accuracy and complexity.
Solution Approach 2:
The patent applies different processing quality to different frames based on their characteristics. Frames with significant picture changes (key frames) receive enhanced processing and attention, while ordinary frames use standard uniform capture algorithms, optimizing both detection accuracy and processing complexity.
3Loss of time
If all video frames are decoded, then decoding accuracy is maintained, but time consumption increases
Solution Approach 1:
The patent extracts and identifies key frames from the video sequence based on frame attributes and importance criteria. By separating key frames from non-key frames, the system can focus decoding resources on extracting accurate information from key frames while using faster differential decoding for non-key frames, reducing overall time while maintaining accuracy for critical content.
Solution Approach 2:
Instead of applying full decoding processing to all frames, the patent applies partial decoding (differential decoding) to non-key frames where full accuracy is less critical, and reserves excessive/full decoding action for key frames where accuracy is paramount. This selective approach reduces total decoding time while preserving accuracy where needed.
Data Source
AI summary
A video decoding method includes performing video stream analysis on a to-be-decoded video to obtain a frame data packet of video frames in the to-be-decoded video; determining frame types of the video frames based on frame attribute information in the frame data packet; determining target sampling frames from the to-be-decoded video based on a quantity of key frames; obtaining rendering data from frame buffers; and performing video decoding on the to-be-decoded video based on the rendering data to obtain a decoded video corresponding to the to-be-decoded video.