Video Stream Latency Measurement with Feature Correlation
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Solution Overview
Problem
Existing methods for real-time latency measurement between video streams are cumbersome and time-consuming, often involving manual frame alignment or complex frame-based measurements that are impractical.
Innovation Solution
A feature-based technique using spatial and temporal information extraction and correlation analysis is employed to synchronize and measure latency between video streams, utilizing filters like Gaussian and Laplacian filters, and correlation metrics such as Pearson Linear Correlation Coefficient to align and calculate latency accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual frame alignment or frame-based measurement is used, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The patent extracts and analyzes only specific key features (spatial information, temporal information, motion vectors) from video frames rather than processing entire frames. This selective extraction maintains measurement precision while significantly reducing computational complexity and improving measurement speed.
Solution Approach 2:
The patent segments the video frame analysis into distinct feature components (spatial features, temporal features, motion vectors) that can be processed independently and efficiently. This segmentation allows for optimized computation of each feature type, resolving the contradiction between precision and speed.
2Measurement precision
If manual frame alignment is used, then measurement precision is improved, but device complexity deteriorates
Solution Approach 1:
The patent replaces manual visual frame alignment with an automated computational system that uses feature extraction and correlation analysis. This substitution eliminates the need for human operators while maintaining or improving measurement precision, and the systematic approach actually reduces overall complexity compared to manual procedures.
3Measurement precision
If frame-based measurement is used, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements a self-service measurement system that automatically performs feature extraction, correlation analysis, and latency calculation without requiring manual frame-by-frame inspection. The system autonomously identifies corresponding frames and computes latency, making the operation simple while maintaining high precision through rigorous feature-based comparison.
Data Source
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AI summary
Frames of a video stream collected at first and second points along a video delivery chain are buffered into first and second buffers, respectively, the second point being downstream the video delivery chain from the first point. A control group is identified as a subset of frames of the second buffer. Correlations of extracted features of the control group to extracted features of successive windows of frames of the first buffer are computed, the extracted features being based on spatial information and temporal information of the video stream. A delay between the video stream collected at the first point and the video stream collected at the second point is identified according to a maximum correlation of the correlations.