Camera Pose Estimation Using Orientation Sensors and Image Features
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Solution Overview
Problem
Existing methods for determining the pose of a camera in augmented reality applications are either resource-intensive, require pre-conceived virtual reference models or user-placed markers, or struggle with absolute pose estimation in unknown environments, making them unsuitable for spontaneous use in consumer devices like mobile phones.
Innovation Solution
A method that uses orientation sensors and image analysis to generate orientation and distance data, allowing for user-interaction to determine the camera's pose relative to a coordinate system, which can be integrated into mobile devices with minimal processing requirements, enabling augmented reality without prior environmental knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If virtual reference models are used for pose determination, then measurement precision is improved, but device complexity and processing requirements increase significantly
Solution Approach 1:
The patent extracts the essential function of pose determination from complex virtual reference models and marker systems. Instead of using full 3D models or artificial markers, the invention uses simple geometric primitives (planes, lines, points) extracted directly from the image data itself, eliminating the need for external reference databases while maintaining measurement precision
Solution Approach 2:
The patent creates a simplified copy of the environment by extracting geometric features (planes, lines, points) directly from the captured image. This copy is sufficient for pose determination without requiring complete virtual reference models, significantly reducing processing requirements while maintaining accuracy
2Measurement precision
If markers are placed in the real environment for pose determination, then measurement precision is improved, but ease of operation deteriorates due to additional setup steps
Solution Approach 1:
The system performs self-service by extracting its own reference features from the captured image data. The image processing algorithms automatically identify geometric primitives (planes, lines, points) within the scene, eliminating the need for external markers or manual setup. The system uses the environment's natural geometric structures as references
Solution Approach 2:
The patent performs preliminary extraction of geometric features from the image data before pose determination. By pre-identifying planes, lines, and points in the captured image, the system prepares all necessary reference information in advance, enabling immediate pose calculation without additional setup steps
3Adaptability or versatility
If structure from motion or SLAM methods are used, then adaptability to unknown environments is improved, but measurement precision of absolute pose deteriorates
Solution Approach 1:
The patent replaces complex iterative optimization methods (mechanical systems) with direct geometric calculations. Instead of using SLAM's iterative state estimation or structure from motion's complex bundle adjustment, the invention uses straightforward geometric relationships between extracted features and camera parameters to directly compute pose, improving both speed and absolute pose accuracy
Solution Approach 2:
The patent changes the approach from estimating pose through iterative optimization of multiple parameters to directly calculating pose from geometric primitives. By focusing on essential geometric relationships (planar homography, line intersections, point correspondences), the system achieves accurate absolute pose determination without the computational overhead of traditional methods
4Measurement precision
If multiple images are required for pose determination, then measurement precision is improved, but productivity decreases due to longer processing time
Solution Approach 1:
The patent uses partial action by extracting only the essential geometric features (planes, lines, points) needed for pose determination from the image, rather than processing all image data. This selective feature extraction maintains measurement precision while significantly reducing processing time and computational requirements
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces processing needs and allows for rapid pose estimation, enabling augmented reality applications on mobile devices without the need for pre-defined models or markers, facilitating spontaneous use in various environments.
Implementation Method 1
generating first orientation data from at least one orientation sensor associated with the camera
Implementation Method 2
from an algorithm which analyses the first image for finding and determining features which are indicative of an orientation of the camera
Data Source
AI summary
Method for determining the pose of a camera with respect to an object of a real environment for use in authoring/augmented reality application that includes generating a first image by the camera capturing a real object of a real environment, generating first orientation data from at least one orientation sensor associated with the camera or from an algorithm which analyzes the first image for finding and determining features which are indicative of an orientation of the camera, allocating a distance of the camera to the real object, generating distance data indicative of the allocated distance, determining the pose of the camera with respect to a coordinate system related to the real object of the real environment using the distance data and the first orientation data. May be performed with reduced processing requirements and/or higher processing speed, in mobile device such as mobile phones having display, camera and orientation sensor.