Video Feed Synchronization via Discontinuity Detection
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Solution Overview
Problem
Conventional methods for synchronizing multiple video feeds from diverse camera sources, such as smartphones, are computationally intensive and inefficient, especially when these feeds lack embedded time codes and have different frame rates, resolutions, and orientations, leading to the need for human intervention and high computational complexity.
Innovation Solution
A system and method that utilize discontinuities in video feeds, such as changes in motion or audio, to synchronize and time-align multiple video streams by detecting common discontinuities across feeds, reducing computational requirements and enabling automated synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to synchronize multiple video feeds from diverse camera sources, then synchronization accuracy can be maintained, but computational complexity increases significantly and human intervention is required
Solution Approach 1:
The system enables automated synchronization by allowing video feeds to self-align through automatic detection of common discontinuities. The synchronization process does not require human intervention - the system autonomously identifies temporal offsets by detecting matching discontinuity patterns across multiple feeds and applies corrections automatically.
Solution Approach 2:
The method extracts only the essential synchronization information from video feeds by identifying common discontinuities (sudden changes in pixel values). Instead of processing entire video frames or complex temporal data, the system isolates and uses only the discontinuity patterns, significantly reducing computational requirements while maintaining synchronization accuracy.
2Extent of automation
If automated synchronization methods are implemented, then human intervention is reduced, but handling feeds with different frame rates and resolutions becomes more complex
Solution Approach 1:
The system handles diverse feed characteristics by changing the analysis parameter from frame-based to discontinuity-based. Instead of requiring uniform frame rates and resolutions, the method detects discontinuities (sudden pixel value changes) which are invariant to these parameters. This allows automated synchronization of feeds with different technical specifications by focusing on the temporal patterns of discontinuities rather than frame structures.
3Measurement precision
If video feeds are processed in detail to ensure accurate synchronization, then synchronization precision improves, but processing time increases
Solution Approach 1:
The method extracts only the essential synchronization information from video feeds by identifying common discontinuities. Instead of processing entire video frames or complex temporal data, the system isolates and uses only the discontinuity patterns, significantly reducing computational requirements and processing time while maintaining synchronization precision.
Solution Approach 2:
The system applies partial action by processing only the necessary portions of video data - specifically, only the discontinuity points are analyzed for synchronization. Rather than examining every frame or pixel, the method focuses exclusively on the critical discontinuity events, achieving accurate synchronization with minimal processing effort.
Data Source
AI summary
Embodiments of the present invention provide a system and method to automatically generate synchronization points based on a common characteristic given a plurality of random video feeds. The common characteristic can be based on changes in motion, audio, image, etc between the feeds. A feedback process attempts to time align the synchronized video outputs based on discontinuities in the feeds. Once the video feeds are time aligned, the aligned content can be used for recreating a multi-view video montage or feeding it into a 3-D correlation program.