Distributed Video Stream Calibration via Client-Side Metadata
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Solution Overview
Problem
Existing communication systems face challenges in addressing visual anomalies in video streams from diverse sources, leading to inconsistent and inefficient use of computing resources, particularly during large-scale events, due to the need for centralized processing and analysis of lighting and display characteristics.
Innovation Solution
A system that generates calibration metadata based on device specification data, allowing client devices to analyze and adjust their video streams according to a normalized standard, thereby reducing the computational burden on central servers and improving video stream consistency without requiring continuous server intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a central server analyzes and normalizes display characteristics of each video stream, then visual anomalies are corrected, but computing resources and power consumption increase significantly
Solution Approach 1:
The patent divides the video stream analysis and normalization task into segments performed by individual client devices rather than centralized server processing. Each client device independently analyzes its own video stream characteristics and applies corrections locally, segmenting the computational workload across multiple distributed devices to reduce overall server resource consumption while maintaining visual anomaly correction effectiveness.
2Stability of the object's composition
If a central server processes video streams from multiple sources, then coordinated display is achieved, but system complexity and processing time increase
Solution Approach 1:
Instead of having the central server process and normalize video streams from multiple sources, the patent inverts the approach by having each client device independently analyze and normalize its own video stream using received calibration metadata. This inversion of the processing direction eliminates the need for complex centralized video analysis while achieving coordinated display consistency through distributed client-side processing.
3Manufacturing precision
If real-time video analysis is performed during large-scale events, then visual quality is maintained, but resource consumption becomes unsustainable
Solution Approach 1:
The patent enables client devices to perform self-service video stream analysis and normalization by providing them with calibration metadata containing display characteristics of other devices. Each client device independently determines appropriate video stream adjustments without requiring real-time server analysis, allowing the system to scale to large-scale events sustainably while maintaining consistent video quality across all participants.
Data Source
AI summary
A system can minimize the use of a central computing resource while detecting and correcting visual anomalies that may result from a compilation of video streams from a variety of sources. The central resource can receive device specification data defining parameters on how remote computers measure image properties and generate video data, e.g., camera sensitivity levels, image generation capabilities, etc. The central resource then uses the device specification data to generate calibration metadata that allows each client device to analyze light levels and generate image data according to a normalized standard. This allows each of the clients to generate more consistent video images to be shared in a video communication session. In some configurations, the calibration metadata causes each client device to make the adjustments automatically, and in some instances, video streams can be corrected according to a ranked list of adjustments.