Hybrid AR Positioning Using Visual Markers and Sensor Fusion
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Solution Overview
Problem
Existing mobile augmented reality systems face challenges with suboptimal rendering APIs, complex real-time marker/markerless systems, and inaccurate sensor data, which hinder seamless integration of live camera imagery and virtual overlays, especially in outdoor environments.
Innovation Solution
A hybrid approach combining GPS, digital compass, and gyroscope data with a modified markerless feature tracking algorithm, along with a nested view transformation matrix for rendering, and a grid-based data storage system to enhance location accuracy and reduce computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS-based location tracking is used for augmented reality, then location awareness is achieved, but measurement precision deteriorates due to line-of-sight requirements and urban blockage
Solution Approach 1:
The patent combines GPS-based location tracking with visual marker recognition to create a hybrid positioning system. The GPS provides coarse location data while visual markers provide precise position and orientation information, compensating for GPS limitations in urban environments without line-of-sight to satellites.
Solution Approach 2:
Visual markers serve as intermediary objects that mediate between the physical environment and the digital overlay system. These markers provide a reliable reference frame for position identification that works independently of satellite signal availability, enabling accurate augmented reality rendering in GPS-denied environments.
2Adaptability or versatility
If real-time markerless feature tracking is implemented, then adaptability to environments without markers is improved, but device complexity increases due to computational requirements
Solution Approach 1:
The system performs preliminary placement of visual markers in the environment before the augmented reality session begins. This pre-prepared infrastructure eliminates the need for complex real-time markerless feature tracking algorithms, as the system can simply detect and track the pre-placed markers which are optimized for quick and accurate recognition.
Solution Approach 2:
Instead of performing complex real-time analysis of natural features in the environment, the system uses simplified copies in the form of standardized visual markers. These markers are designed with specific patterns that are easy to detect and track, replacing the need for sophisticated natural feature extraction and matching algorithms.
3Measurement precision
If multiple sensors (GPS, gyroscope, accelerometer) are integrated for position identification, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The visual markers themselves encode position and orientation information in their visual patterns, allowing the system to self-determine location without requiring complex integration of multiple sensors. The markers provide intrinsic reference information that simplifies the positioning task, reducing reliance on sophisticated sensor fusion algorithms.
Data Source
AI summary
A system, method, and computer program product for automatically combining computer-generated imagery with real-world imagery in a portable electronic device by retrieving, manipulating, and sharing relevant stored videos, preferably in real time. A video is captured with a hand-held device and stored. Metadata including the camera's physical location and orientation is appended to a data stream, along with user input. The server analyzes the data stream and further annotates the metadata, producing a searchable library of videos and metadata. Later, when a camera user generates a new data stream, the linked server analyzes it, identifies relevant material from the library, retrieves the material and tagged information, adjusts it for proper orientation, then renders and superimposes it onto the current camera view so the user views an augmented reality.