AR Context Granularity Adjustment via Distance
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Solution Overview
Problem
Augmented reality (AR) guidance can be overly broad or narrow for users, leading to frustration, as existing systems fail to dynamically adjust contextual information and interactive options based on the user's distance from an activity location, resulting in inefficient assistance trajectories.
Innovation Solution
A computer-implemented method determines context granularity by ascertaining the user's activity and distance from the activity location, using a machine-learning algorithm to update and display relevant contextual information and interactive options in real-time, supported by wearable AR interfaces, and utilizing historic data to optimize information display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If contextual information and interactive options are displayed at a fixed granularity level, then the AR interface is simple to implement, but the guidance becomes overly broad or narrow for users at different distances
Solution Approach 1:
The system dynamically adjusts the granularity level of contextual information and interactive options based on the user's real-time distance from the activity location. The granularity level transitions from coarse to fine as the user approaches the location, and vice versa, creating an adaptive AR interface that automatically adapts to user proximity without requiring manual configuration.
Solution Approach 2:
The system changes the parameter of contextual information granularity based on distance measurements. Different granularity levels are selected and displayed according to the user's distance from the activity location, transforming the static information display into a dynamic parameter-adjusted system that optimizes information density based on spatial context.
2Measurement precision
If contextual information granularity is continuously adjusted based on distance, then guidance precision is improved, but information processing complexity increases
Solution Approach 1:
The system pre-establishes multiple granularity levels of contextual information and their corresponding distance thresholds before execution. During operation, the system only needs to compare the measured distance against pre-defined thresholds and select the appropriate pre-computed granularity level, avoiding the need for complex real-time calculations while maintaining precise distance-based adaptation.
Solution Approach 2:
The system continuously measures the user's distance from the activity location and uses this feedback to adjust the displayed contextual information granularity level. This closed-loop feedback mechanism ensures that the information display remains precisely aligned with the user's real-time spatial context, improving guidance accuracy through continuous adaptation.
3Loss of information
If detailed contextual information is displayed at all times, then information completeness is improved, but user attention is overwhelmed regardless of distance
Solution Approach 1:
The system applies partial action by displaying only the necessary level of contextual information detail based on the user's distance from the activity location. At greater distances, fewer details are displayed; as the user approaches, progressively more details are revealed. This prevents information overload at all times while ensuring sufficient information completeness when needed.
Solution Approach 2:
The information display dynamically adapts its level of detail based on real-time distance measurements. The system transitions between different information density states automatically as the user moves closer to or farther from the activity location, managing user attention by revealing detailed information only when the user is sufficiently close to process it effectively.
Data Source
AI summary
A computer-implemented method for determining context granularity is provided. The computer-implemented method includes determining an activity for a user and a distance between the user and a location of the activity, ascertaining a contextual information granularity level for displaying contextual information relevant to the activity in an augmented reality (AR) interface in accordance with the distance, displaying the contextual information corresponding to the contextual information granularity level in the AR interface, updating the contextual information granularity level as the distance changes to obtain a new contextual information granularity level and displaying the contextual information corresponding to the new contextual information granularity level in the AR interface.