Video Transcoding Quality Detection via Embedded Test Objects
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional video transcoding methods often result in issues such as frame loss, frame drop, and sound and picture non-synchronization, which negatively impact the video viewing experience, and existing quality evaluation systems like PSNR, SSIM, and VMAF are inadequate in detecting these problems.
Innovation Solution
A video processing method that sets a test object with video parameters in each frame of the original video, transcodes it, and compares the parameters before and after transcoding to determine if frame loss, frame drop, or sound and picture non-synchronization has occurred, using a video processing device with modules for receiving, transcoding, object extraction, and result determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional video transcoding is performed, then video format conversion is achieved, but frame loss, frame drop, and sound-picture non-synchronization occur
Solution Approach 1:
The patent embeds test objects containing video parameters into the original video frames before transcoding. This preliminary action enables subsequent verification of transcoding quality by comparing the embedded parameters before and after the transcoding process, thereby detecting frame loss, frame drop, and sound-picture synchronization issues.
Solution Approach 2:
The patent establishes a feedback mechanism where transcoded video frames are extracted and their embedded parameters are compared with the original parameters. This feedback loop enables automatic detection and evaluation of transcoding quality, allowing the system to identify specific issues such as frame loss and synchronization problems.
2Measurement precision
If existing quality evaluation systems (PSNR, SSIM, VMAF) are used, then general video quality assessment is provided, but detection of frame loss, frame drop, and sound-picture non-synchronization is inadequate
Solution Approach 1:
The patent extracts specific video parameters embedded in test objects from video frames, separating the detection of transcoding issues from general video quality assessment. This extraction approach enables targeted detection of frame loss, frame drop, and synchronization problems without relying on conventional metrics like PSNR, SSIM, or VMAF.
Solution Approach 2:
The patent uses embedded test objects as intermediaries to transfer video parameter information through the transcoding process. These test objects serve as carriers that preserve parameter data, enabling verification of transcoding quality by comparing parameters before and after transcoding without directly analyzing the video content itself.
3Measurement precision
If video parameters are compared before and after transcoding, then accurate detection of transcoding issues is achieved, but additional processing steps are required
Solution Approach 1:
The patent merges the video parameter verification process with the existing transcoding workflow by embedding parameters directly into video frames during the transcoding process itself. This integration allows quality detection to occur within the same processing pipeline rather than as a separate post-processing step, reducing overall system complexity.
Solution Approach 2:
The patent enables the video transcoding system to self-verify its output quality by comparing embedded parameters before and after transcoding. This self-service mechanism allows the system to automatically detect and report transcoding issues without requiring external verification tools or additional complex processing systems.
Data Source
AI summary
The present disclosure describes techniques of processing video. The techniques comprise obtaining a video to be transcoded, the video comprising a plurality of frames; setting a test object in each of the plurality of frames of the video to be transcoded; transcoding the video using a predetermined video transcoding mechanism and obtaining the transcoded video; extracting a test object from each of a plurality of frames of the transcoded video; and determining a transcoding result based at least in part on the test object extracted from each of the plurality of frames of the transcoded video.