AR Data Processing Prioritizing Object Recognition
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Solution Overview
Problem
In augmented reality environments, existing technologies face challenges in effectively prioritizing and modifying virtual objects based on recognized objects in the real world, leading to potential obfuscation of critical real-world information by virtual overlays.
Innovation Solution
A method and system that prioritize object recognition data from a secure trust level over augmented reality data, allowing for the modification of virtual objects to ensure that recognized objects in the real world are not obscured, by using a secure processor to intercept and modify augmented reality data based on object recognition inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If augmented reality data is displayed to enhance user experience, then user engagement and information delivery are improved, but critical real-world objects may be obscured by virtual overlays
Solution Approach 1:
The system performs object recognition and determines visibility requirements before rendering augmented reality content. By pre-identifying critical real-world objects and their classification, the system can proactively adjust AR overlay transparency or positioning to prevent obscuration of important elements such as pedestrians or traffic signals.
Solution Approach 2:
The system applies different transparency or visibility properties to different regions of the augmented reality display based on local object characteristics. Critical objects in specific spatial locations receive enhanced visibility treatment (higher transparency or priority rendering) while non-critical areas maintain full AR overlay enhancement, creating spatially varying quality properties.
2Reliability
If object recognition systems process all detected objects, then comprehensive environmental awareness is achieved, but processing time and computational resources increase
Solution Approach 1:
The system performs partial object recognition by focusing computational resources on identifying and classifying only those objects that are relevant to safety and navigation (e.g., pedestrians, vehicles, traffic signals) rather than processing all detected objects equally. This selective approach maintains reliability for critical functions while reducing overall processing time.
Solution Approach 2:
The object recognition system segments processing into multiple priority levels or categories. Critical objects (safety-related) are processed with high priority and detailed analysis, while non-critical objects receive minimal processing or are aggregated into general environmental context, dividing the computational task into manageable segments with different resource allocations.
Data Source
AI summary
A method of data processing for an augmented reality system. The method comprises obtaining augmented reality data output by an augmented reality application operating at a second trust level. The augmented reality data is for modifying a representation of a real-world environment for a user of the augmented reality system. The method also comprises obtaining object recognition data determined by an object recognition system operating at a first trust level. The object recognition data comprises an indication of an object belonging to a predetermined class of objects being present in the real-world environment. The method also comprises triggering modification of the augmented reality data in response to the object recognition data, based on prioritization of the first trust level over the second trust level.