AR Street Annotation Segmentation for Complex Intersections
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Solution Overview
Problem
Augmented reality systems face challenges in effectively annotating streets in a first-person perspective, making it difficult for users to correlate real-world views with street information, especially in complex intersections and while navigating on foot.
Innovation Solution
The system determines which streets to annotate and how to format the annotations based on user distance, orientation, and street configurations, using zones to differentiate between 3D and 2D annotations, and selectively annotating street segments to reduce visual clutter and improve readability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all visible and/or intersecting streets are annotated, then the user receives comprehensive street information, but visual clutter increases and becomes difficult for the user to decipher
Solution Approach 1:
The patent segments street annotations by creating zones based on distance from the user. Streets within a first zone (closer) are annotated with a first format, streets in a second zone (farther) are annotated with a second format, and streets beyond a threshold distance are not annotated. This segmentation reduces visual clutter while maintaining comprehensive information for relevant streets.
Solution Approach 2:
The patent applies different annotation formats to different spatial regions. Streets in the first zone receive annotations with a first format (e.g., larger, more prominent), while streets in the second zone receive annotations with a second format (e.g., smaller, less prominent). This local differentiation allows comprehensive information display while managing visual clutter through format variation.
2Loss of information
If street annotations are provided for complex intersections with three or more streets, then the user receives complete intersection information, but it becomes difficult for the user to correctly correlate streets with real-world views
Solution Approach 1:
The patent segments intersection streets into different zones based on distance from the user. By annotating streets in the first zone with a distinct first format and streets in the second zone with a second format, the system helps users correlate annotations with the actual spatial layout of the complex intersection, improving ease of operation.
Solution Approach 2:
The patent introduces a spatial dimension (distance-based zones) to organize intersection annotations. This creates a hierarchical structure where proximity to the user determines annotation format, helping users mentally map the complex intersection geometry and correctly correlate street names with their real-world positions.
3Productivity
If the user is walking on sidewalks and needs to navigate, then real-time navigation assistance is needed, but correlating street information with the real-world view becomes especially challenging
Solution Approach 1:
The patent segments the environment into zones based on distance from the user's current position. Streets in the first zone (closer to the user's path) are annotated with a first format that is more prominent and easier to read, while streets in the second zone are annotated with a second format. This segmentation improves navigation efficiency by highlighting relevant streets while maintaining view-correlation ease through format differentiation.
Data Source
AI summary
Systems, methods, and and/or algorithms facilitate navigation with augmented reality by determining which streets should be annotated, and/or determining the position and/or format of street annotations, based on factors such as user distance and orientation relative to streets, and/or the configuration of streets (e.g., whether nearby streets form a simple intersection, a complex intersection, or no intersection).