Heading Estimation Using Image Line Detection and GPS
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Solution Overview
Problem
Existing methods for determining the location and orientation of devices in computer-generated reality environments, such as GPS and magnetometer-based systems, lack the necessary accuracy for precise pose estimation in complex environments.
Innovation Solution
The implementation of computer vision algorithms, specifically image processing methods that detect lines in a scene, to enhance the accuracy of device orientation estimation, combining this with geographic location data to determine the heading of a device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS and magnetometer-based systems are used for location and orientation determination, then the system can operate globally, but the accuracy of pose estimation deteriorates in complex environments
Solution Approach 1:
The patent combines multiple sensing systems (GPS, magnetometer, and computer vision algorithms) into a unified pose estimation system. The image processing module detects lines and features in captured images, while the processor integrates this visual data with GPS and magnetometer information to compute accurate heading and pose, thereby resolving the accuracy problem in complex environments without sacrificing global operability.
Solution Approach 2:
The patent introduces an intermediary computer vision processing layer that mediates between the raw sensor data from GPS and magnetometer and the final pose estimation. This intermediary module processes image data to extract orientation information, which then refines the pose calculation, effectively improving measurement precision while managing system complexity through modular architecture.
2Measurement precision
If traditional GPS and magnetometer systems are used, then the system is simple to implement, but the measurement precision of location and orientation is insufficient
Solution Approach 1:
The patent segments the pose estimation system into distinct functional modules: a GPS module for global positioning, a magnetometer module for orientation, and a computer vision module for local orientation refinement. Each module processes specific sensor data independently, then the processor integrates their outputs. This segmentation allows the system to achieve high measurement precision through specialized processing while managing complexity through modular design.
Solution Approach 2:
The patent creates a composite sensing system that combines multiple data sources (GPS coordinates, magnetometer readings, and image-based orientation data) to form a comprehensive pose estimation. This composite approach leverages the strengths of each sensor type, achieving superior location and orientation precision by synthesizing information from heterogeneous sources rather than relying on a single simple system.
3Measurement precision
If image processing algorithms are added to enhance pose estimation accuracy, then measurement precision improves, but processing time and computational complexity increase
Solution Approach 1:
The patent applies partial action by focusing the computer vision processing on specific tasks rather than complete image analysis. The system detects and processes only the line features and orientation information necessary for heading estimation, rather than performing comprehensive image understanding. This selective processing approach improves measurement precision for heading accuracy while minimizing unnecessary computational time and processing overhead.
Data Source
AI summary
In one implementation, a method of estimating the heading of a device is performed by the device including a processor, non-transitory memory, and an image sensor. The method includes determining a geographic location of the device. The method includes capturing, using the image sensor, an image at the geographic location. The method includes detecting one or more lines within the image. The method includes determining a heading of the device based on the one or more lines and the geographic location.