Visual Marker Positioning for More Accurate Mobile Geolocation
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Solution Overview
Problem
Existing systems for determining the location of mobile electronic devices using visual markers, such as QR codes, lack accuracy and often rely solely on locally-determined GPS data, which can be imprecise.
Innovation Solution
Utilizing computer vision techniques like VIO and SLAM to determine relative positioning between a mobile device and a visual marker, combined with crowd-sourced location data from multiple devices, to enhance the accuracy of geolocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standalone GPS or local sensors are used to determine device location, then the system is simple and easy to operate, but the location accuracy is insufficient
Solution Approach 1:
The patent combines multiple positioning methods (GPS, visual markers with VIO/SLAM/PNP techniques, and local sensors) into a unified location determination system. The system merges data from different sources to achieve higher accuracy while managing complexity through integrated processing architecture.
Solution Approach 2:
Visual markers serve as intermediary elements that bridge the device's local sensing system with external reference frames. The markers provide known position information that enables the system to anchor and refine location calculations, improving accuracy without requiring the device to directly measure absolute positions.
2Measurement precision
If visual markers with computer vision techniques are used to determine location, then location accuracy is improved, but the system complexity increases
Solution Approach 1:
The patent segments the location determination task into distinct modules: visual marker detection, relative positioning calculation (using VIO/SLAM/PNP), and location refinement. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by dividing complex processing into manageable stages.
Solution Approach 2:
The system performs preliminary actions by pre-establishing visual markers with known locations in the environment. This preparation enables the device to use these pre-positioned references for accurate location determination without requiring complex real-time measurements, reducing the computational burden during actual location queries.
3Measurement precision
If multiple positioning methods are combined for higher accuracy, then location precision improves, but the processing time increases
Solution Approach 1:
The patent applies partial action by selectively using different positioning methods based on availability and requirements. The system uses visual markers and computer vision techniques when markers are detected, while falling back to GPS or sensor-based methods when markers are not visible, thus avoiding unnecessary processing time while maintaining accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where location data from visual markers is used to refine and correct GPS or sensor-based position estimates. This feedback loop allows the system to iteratively improve accuracy while reducing processing time by using corrections from high-accuracy sources to adjust less accurate measurements.
Data Source
AI summary
Various implementations disclosed herein include devices, systems, and methods that determine the relative positioning (e.g., offset) between a mobile electronic device and a visual marker. In some implementations, the determined relative positioning and a known position of the visual marker are used to determine a position (e.g., geo coordinates) of the mobile electronic device that is more accurate than existing techniques. In some implementations, the determined relative positioning is used with a position of the mobile electronic device to crowd source the stored position of the visual marker. In some implementations, the determined relative positioning and a position of the visual marker are used to determine a position of an object detected in an image by the mobile electronic device. In some implementations at an electronic device having a processor, locally-determined locations of a visual marker are received from mobile electronic devices that scan a visual marker.