Streaming Video Timing Anomaly Detection via Motion Data Comparison
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Solution Overview
Problem
Variability in network conditions during media content streaming can lead to jitter, loss, or duplication of data, resulting in inaccurate estimation of media content timing data, causing acceleration or slowdown effects in video and audio playback.
Innovation Solution
The technique involves detecting timing data anomalies by comparing motion data from different temporal portions of media content, determining differences in motion vector histograms, and adjusting playback operations to correct erroneous or missing timing data, such as by requesting new timing data or modifying playback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If timing data is estimated during media content streaming, then playback can continue without interruption, but timing accuracy deteriorates due to network variability and data loss
Solution Approach 1:
The system continuously monitors motion data from video frames and compares it against expected motion patterns to detect timing anomalies. When anomalies are detected, the system adjusts playback timing accordingly, creating a closed-loop feedback mechanism that maintains both continuity and accuracy despite network variability
Solution Approach 2:
The patent replaces reliance on network-provided timing data (mechanical/system-dependent) with physics-based motion analysis from video content itself. By analyzing motion vectors and temporal consistency in video frames, the system derives timing information independently of network conditions, substituting an unreliable external timing source with an intrinsic content-based timing mechanism
2Manufacturing precision
If timing data correction is implemented, then playback quality improves, but system complexity increases due to additional detection and correction mechanisms
Solution Approach 1:
The motion analysis module serves multiple functions: it is used for normal video processing, timing anomaly detection, and playback synchronization. By making this single component multi-functional, the system achieves accurate timing correction without adding separate dedicated mechanisms, thereby limiting the increase in system complexity
Solution Approach 2:
The system uses its own video processing pipeline to generate timing correction information. The same motion estimation algorithms used for video compression and rendering are repurposed to detect timing anomalies and calculate corrections, allowing the system to self-diagnose and self-correct timing issues without external intervention or additional specialized hardware
3Measurement precision
If motion data analysis is performed for timing detection, then timing anomaly detection accuracy improves, but processing time increases
Solution Approach 1:
Motion data is extracted and analyzed in advance during video decoding and rendering preparation, before playback occurs. By performing timing anomaly detection ahead of time, the system identifies and corrects timing issues without adding processing delays during actual playback, thus maintaining both high detection accuracy and real-time performance
Data Source
AI summary
Techniques are described for detecting timing data anomalies in streaming video. Techniques are also described for adjusting playback operations based on detecting possible timing data anomalies.