Augmented Reality Object Enhancement Thresholds
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Solution Overview
Problem
Augmented reality environments fail to effectively enhance objects in a user's view based on their probability of interaction, particularly for users with physical constraints such as color blindness, where dynamic adjustments to the environment are costly and inefficient.
Innovation Solution
A computer-implemented method that obtains a user profile with constraints, determines the user's intent and path, calculates the probability of interaction with objects, and generates enhancement thresholds to dynamically adjust the appearance of objects based on user constraints and predicted interactions, using machine learning for intent prediction and object recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic adjustments to the augmented reality environment are made for all objects, then user experience for users with physical constraints is improved, but computational cost and processing time increase
Solution Approach 1:
The system performs preliminary actions by predicting the user's path and calculating interaction probabilities for objects before the user actually encounters them. This allows the system to pre-determine which objects need enhancement, avoiding real-time computational overhead when the user is actively navigating.
Solution Approach 2:
The enhancement application dynamically adjusts object properties based on real-time factors including user constraints, predicted interaction probability, and current viewing conditions. Objects are enhanced selectively rather than uniformly, with enhancement thresholds adjusted based on calculated probabilities.
2Reliability
If dynamic adjustments to the augmented reality environment are made for all objects, then user experience for users with physical constraints is improved, but computational resources and processing power increase
Solution Approach 1:
The system applies local quality by enhancing only specific objects that meet certain criteria rather than all objects uniformly. Enhancement is applied locally to objects with high interaction probability that are relevant to the user's current context and constraints, leaving other objects unchanged to conserve computational resources.
Solution Approach 2:
The system performs partial action by applying enhancements only to a subset of objects rather than all objects in the environment. The enhancement threshold mechanism ensures that only objects exceeding a certain probability threshold receive enhancement, reducing overall computational load while maintaining user experience quality.
3Reliability
If enhancement thresholds are calculated for all objects, then object visibility for users with constraints is improved, but system complexity increases
Solution Approach 1:
The system calculates enhancement thresholds in advance based on predicted user paths and interaction probabilities, rather than calculating them on-demand during user interaction. This preliminary calculation reduces real-time system complexity while maintaining accurate enhancement decisions.
Solution Approach 2:
The system uses the user's own profile data, including their specific constraints, to automatically determine appropriate enhancement levels. The user profile serves as a self-describing document that guides the enhancement process without requiring complex external configuration or manual intervention.
Data Source
AI summary
A computer-implemented method, a computer system and a computer program product enhance user interaction with a virtual or augmented environment. The method includes obtaining a user profile. The user profile includes a constraint of a user. The method also includes identifying a plurality of objects in the augmented reality environment. In addition, the method includes determining an intent of the user with respect to navigating the augmented reality environment. The method further includes calculating a probability of interaction between the user and an identified object based on the intent. Lastly, the method includes generating an enhancement threshold for each of the identified objects based on the probability of interaction and the constraint of the user.