Gaze-Tracked Area-of-Interest Information Sharing for Limited Visibility
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Solution Overview
Problem
In collaborative environments, individuals often struggle to communicate effectively due to limited visibility of the area of interest, leading to potential errors and inefficiencies in tasks like surgical procedures or equipment maintenance.
Innovation Solution
A computer-implemented method determines an area of interest within the field of view of one individual and provides indicators or information to another individual if it is not within their view, using gaze tracking and environmental modeling to facilitate better communication and task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If individuals communicate verbally about areas of interest in a shared physical environment, then collaboration is improved, but errors may occur when the second individual cannot see the area of interest
Solution Approach 1:
The system introduces a computational intermediary that processes gaze data, environment models, and communication data to determine whether the area of interest is visible to the second individual. This intermediary automatically provides visual indicators or alternative information when visibility is compromised, resolving the information loss without requiring constant verbal confirmation
Solution Approach 2:
The system implements feedback by monitoring the second individual's field of view through gaze tracking and environment modeling, then providing real-time indicators or alternative information when the area of interest is not visible. This closed-loop feedback ensures collaboration reliability by compensating for visibility gaps
2Productivity
If the system provides visual indicators and information about areas of interest, then communication efficiency is improved, but device complexity increases due to gaze tracking and environment modeling requirements
Solution Approach 1:
The system achieves multi-functionality by using a unified environment model that serves multiple purposes: it represents the physical space for gaze tracking, determines field of view boundaries, identifies areas of interest, and provides the basis for generating visual indicators. This single model structure handles all spatial reasoning tasks without requiring separate complex subsystems
Solution Approach 2:
The system creates a computational copy of the physical environment through the environment model, which replicates spatial relationships, objects, and boundaries. This digital twin allows the system to perform visibility analysis and generate indicators without physically modifying the environment or requiring complex hardware changes
Data Source
AI summary
A mechanism for selectively providing a second individual with information about an area of interest to a first individual. The mechanism determines whether the area of interest falls within a field of view of the second individual. If the area of interest does not fall within this field of view, then appropriate information about the area of interest is provided to the second individual.