Surface-Feature Localization for Consistent Indoor AR Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing techniques for determining 3-D physical or geographic location and pose of a device indoors are limited by accuracy, requiring specific instrumentation, overhead effort, and unsightly fiducial markers, and existing systems fail to provide precise localization without constant monitoring and calibration.
Innovation Solution
A system and method for image-based localization using recognized surface features in a previously scanned physical environment, enabling the creation of a feature search structure for augmented reality features, allowing consistent display across different coordinate systems without the need for absolute geolocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or satellite signals are used for location determination, then outdoor location accuracy is adequate, but indoor location accuracy deteriorates due to signal blockage and reflections
Solution Approach 1:
The patent introduces an intermediary system consisting of overhead cameras and computer vision algorithms that mediate between the device and the location determination process. Instead of relying on satellite signals that are blocked indoors, the system uses visual imagery captured by cameras as an intermediary to identify location-based features and determine device position through image processing and coordinate system transformations.
2Measurement precision
If WiFi routers or Bluetooth beacons are deployed for indoor location determination, then location precision is improved, but device complexity and infrastructure requirements worsen
Solution Approach 1:
The patent applies universality by using overhead surveillance cameras that serve multiple functions: their primary function for security monitoring is maintained, while simultaneously they capture imagery used for location-based feature identification and device localization. This eliminates the need for dedicated location infrastructure like WiFi routers or Bluetooth beacons, as existing camera infrastructure is repurposed for dual functionality.
3Measurement precision
If fiducial markers are placed in the environment for location framework, then location determination accuracy is improved, but ease of operation worsens due to overhead effort and unsightly appearance
Solution Approach 1:
The patent extracts the location determination function from physical fiducial markers and transfers it to digital features identified through computer vision processing of camera imagery. Instead of requiring physical markers to be placed in the environment, the system extracts location-based features from natural or existing visual elements in the scene, eliminating the need for overhead deployment effort and unsightly marker placement while maintaining location determination accuracy.
4Measurement precision
If indoor surveillance cameras are used for location determination, then location accuracy is improved, but device complexity worsens due to constant monitoring and communication requirements
Solution Approach 1:
The patent applies preliminary action by pre-processing camera imagery to identify location-based features and establish coordinate systems before devices need location determination. The system performs image processing, feature extraction, and coordinate system transformations in advance, creating a ready-to-use location framework that devices can query without requiring constant monitoring or real-time communication with the monitoring system, thereby reducing system complexity.
Data Source
Figure 1
Figure 2
AI summary
A system and method can support image based determination of mobile device location through recognition of surface features for a previously scanned physical environment. The system and method can also support authoring and positioning of augmented reality features in an authoring interface using the same images and positions of surface features that are to be used for subsequent mobile device localization. As a result, mobile devices leveraging those same images and positions of surface features for localization will be more likely to obtain a localization that is consistent with the positioning displayed in the authoring interface. Augmented reality features authored using the same scan of the environment can be reliably displayed to an end user of an augmented reality application in a position consistent with their authoring in a common coordinate system, even though the authoring may have been performed remotely, away from the actual situs of the physical environment.