Conference Room Video Stitching for Spatial Context
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Solution Overview
Problem
Existing conference room video systems fail to effectively integrate and display video streams from multiple cameras, leading to disjointed views and lack of spatial context, as they often do not align video information from different sources, limiting the ability to provide a comprehensive and cohesive view of the room.
Innovation Solution
A system that receives and analyzes video streams from multiple sources, identifies feature points such as furniture and participants, and processes the streams to ensure consistency in scale, color, and brightness, then stitches them together to create a unified video stream that can be displayed in the room or remotely, allowing for improved spatial awareness and context during video teleconferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple video streams from different cameras are displayed separately, then each camera's view is clearly visible, but the spatial relationship between different camera views is lost and the overall room context is not provided
Solution Approach 1:
The patent merges multiple separate video streams from different cameras into a single stitched video stream. The processing module combines video data from multiple sources, aligns them based on spatial relationships, and produces one integrated output that preserves spatial context while maintaining visibility of all camera views.
Solution Approach 2:
The patent introduces a processing module as an intermediary between the multiple video sources and the display. This module performs feature point detection, video stream matching, and stitching operations to create the unified spatial context without requiring complex direct integration of all camera systems.
2Loss of information
If video streams from multiple sources are stitched together to provide comprehensive spatial context, then a unified view of the room is achieved, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent performs preliminary feature point detection and extraction from video streams before the stitching process. By pre-identifying key feature points in each video stream, the system reduces the computational complexity of the subsequent matching and alignment operations, making the overall stitching process more efficient.
Solution Approach 2:
The patent segments the video processing task into distinct stages: feature point detection, feature point matching, video stream alignment, and final stitching. This segmentation allows each module to be optimized independently and reduces the overall computational burden compared to processing all video data simultaneously.
3Manufacturing precision
If video streams are processed to ensure consistency in scale, color, and brightness, then the quality and coherence of the stitched video is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent adjusts video stream parameters such as scale, color, and brightness to ensure consistency across all input streams. The processing module detects parameter variations between different video sources and applies corrective transformations to achieve uniform visual quality in the stitched output, improving overall coherence.
4Loss of information
If a unified video stream is generated from multiple sources, then spatial awareness and context are enhanced, but the ability to access individual camera views separately is reduced
Solution Approach 1:
The patent creates a processing module that serves multiple functions: it can generate a stitched video stream for comprehensive spatial context, while also maintaining the capability to output individual video streams when needed. This multi-functionality allows the system to adapt to different viewing requirements without sacrificing either unified spatial context or individual view accessibility.
Data Source
AI summary
Techniques to stitch together multiple video streams are described. In an embodiment, a technique may include receiving a plurality of video streams from a plurality of video sources in a room. The video streams may be analyzed for feature points, such as furniture, light fixtures, window frames and so forth. The video streams may be processed to make the video qualities of the video streams, such as scale, color, brightness and so forth, more consistent with each other. Using the feature points, the processed video streams may be stitched together to generate a unified stream. The unified stream may be output to a display in the room and/or to remote viewers. Other embodiments are described and claimed.