Aggregation Grid for Overcoming Visual Obstructions in Video Feeds
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Solution Overview
Problem
Viewers in environments like classrooms or lecture halls often experience obstructions, such as teachers standing in front of blackboards, which block their view of important information, leading to missed content due to varying angles of view among individuals.
Innovation Solution
A computer-implemented method using wearable devices to capture video feeds from different angles, creating an aggregation grid that identifies obstructed cells and retrieves unobstructed video portions from other devices to display a complete and personalized view on the user's device, overlaying obstructed areas with content from other viewers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple wearable devices capture video feeds from different angles, then the completeness of scene coverage is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The scene is divided into an aggregation grid with multiple cells, where each cell can be independently captured by different wearable devices. This segmentation allows the system to manage complex multi-device data by breaking it down into discrete, manageable units that can be selectively combined to overcome obstructions.
Solution Approach 2:
Video portions from multiple wearable devices are merged into a single aggregated view. The system combines unobstructed video portions from different devices to create a complete scene representation, merging data from multiple sources to eliminate the limitations of individual device perspectives.
2Reliability
If video portions from other devices are obtained and displayed, then the unobstructed view quality is improved, but the network communication and data transmission requirements increase
Solution Approach 1:
The system extracts only the specific video portions corresponding to obstructed cells from the complete video feeds of other wearable devices. Instead of transmitting entire video streams, it isolates and transmits only the necessary rectangular video portions for the obstructed grid cells, significantly reducing data transmission requirements.
Solution Approach 2:
The system performs partial action by obtaining and processing only the specific video portions needed for obstructed cells rather than complete video feeds. This partial processing approach maintains view quality for critical areas while minimizing unnecessary data transmission and processing overhead.
3Measurement precision
If the aggregation grid partitions views into cells, then the precision of obstruction identification is improved, but the processing complexity increases
Solution Approach 1:
The scene view is partitioned into a grid of cells, allowing precise identification of which specific portions are obstructed. This segmentation enables the system to detect obstructions at the cell level rather than treating the entire view as a single unit, improving precision while maintaining manageable processing through modular cell-based operations.
Data Source
AI summary
Collaborative scene sharing for overcoming visual obstructions is provided. Video feeds of a scene are obtained from multiple devices viewing the scene from different angle. An obstruction obstructs portion(s) of the scene from view by a device. An aggregation grid that partitions views of the scene into cells is established and used in providing an aggregated view of the scene to the device. This includes identifying cell(s) of the aggregation grid for which the view by the device is obstructed by the obstruction, and providing to the device video portion(s) obtained from video feed(s) from the multiple devices. The video portion(s) correspond to the cell(s) for which the view by the device is obstructed, and the video feeds from which the video portions are obtained are from other device(s), of the multiple devices, for which the view for the cell(s) is unobstructed.