Encoded Video Quality Detection With Frame-Level Alarm Scores

The patent applies preliminary action by performing quality detection during the encoding process itself, rather than after encoding is complete. The quality detection service analyzes frame-level metrics and generates quality scores while the video is being encoded, allowing for real-time identification of quality issues before they propagate through the entire encoding pipeline. This enables early intervention and correction without requiring additional post-processing resources.

The patent extracts the quality detection function as a separate service that operates independently from the main encoding process. The quality detection service receives encoded video frames and associated metrics from the encoding process, analyzes them separately, and provides quality feedback. This extraction allows quality analysis to be performed using dedicated resources without burdening the encoding process itself, resolving the contradiction between quality assessment needs and encoding resource constraints.

The patent replaces the mechanical system of manual human review with an automated quality detection service that uses algorithmic analysis of frame-level metrics. The service calculates quality scores based on objective measurements of video frames, replacing subjective human assessment with consistent, automated computational analysis. This substitution maintains high detection accuracy while eliminating the time consumption and productivity losses associated with manual review processes.

The patent implements self-service by enabling the encoding system to automatically detect and identify quality issues without requiring external manual intervention. The quality detection service continuously monitors encoded video output, automatically generates quality scores, and flags segments that meet quality thresholds. This self-monitoring capability allows the system to maintain high detection accuracy while preserving encoding throughput, as the detection process operates autonomously without human involvement.

The patent applies segmentation by dividing the video content into discrete frames and analyzing quality metrics at the frame level. The quality detection service processes individual frames independently, calculating quality scores for each frame based on frame-level metrics such as PSNR, SSIM, or other video quality measurements. This segmentation enables comprehensive quality analysis across the entire video while managing complexity through modular, frame-by-frame processing rather than requiring complex analysis of the entire video as a single unit.

The patent implements partial action by focusing quality detection on specific frame-level metrics and key quality indicators rather than performing exhaustive analysis of all possible video attributes. The quality detection service selectively measures relevant quality parameters (such as PSNR, SSIM, or encoder-specific metrics) and uses these partial measurements to generate overall quality scores. This approach achieves sufficient quality detection completeness without the excessive complexity and processing requirements of comprehensive full-spectrum video analysis.