Object Marker Arrangement Determination via Triangulation
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Solution Overview
Problem
Conventional surgical navigation systems require a pre-defined marker arrangement for tracking objects, which can be cumbersome and time-consuming, especially when manufacturing tolerances are large, and accuracy depends on user alignment.
Innovation Solution
A method to determine the arrangement of object markers on non-parallel surfaces using a reference device with a pre-determined pattern, where image data from different viewing angles is used to calculate marker positions relative to the reference pattern, allowing for optical detection and accurate tracking without the need for pre-defined marker arrangements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a pre-defined marker arrangement is used for tracking, then the tracking system can identify markers and track movement, but the process becomes cumbersome and time-consuming when manufacturing tolerances are large
Solution Approach 1:
The system performs self-calibration by automatically capturing images of markers from multiple angles and computing their 3D positions through triangulation, eliminating the need for manual pointer alignment by the user. The tracking system determines its own marker arrangement parameters autonomously based on captured image data and geometric relationships.
Solution Approach 2:
The manual mechanical alignment process using a trackable pointer is replaced with an optical imaging and computational geometry system. The system uses cameras to capture marker positions and automatically computes 3D coordinates through triangulation algorithms, substituting manual mechanical operations with automated optical-mechanical systems.
2Measurement precision
If a tracked pointer is used to determine each marker position, then the marker arrangement can be determined, but the accuracy depends on user alignment ability
Solution Approach 1:
The system eliminates the need for user alignment operations by automatically capturing images of markers from multiple viewing angles and computing their positions through triangulation. The tracking system independently determines marker coordinates without requiring manual pointer alignment, improving both ease of operation and measurement precision.
Solution Approach 2:
The system introduces an intermediary computational process that bridges the gap between raw image data and accurate marker positions. By using triangulation algorithms that process images from multiple angles, the system achieves high precision without requiring manual alignment, as the computational intermediary automatically resolves positional accuracy.
3Adaptability or versatility
If markers are arranged on non-parallel surfaces, then the object can be tracked from multiple angles, but determining marker positions becomes more complex
Solution Approach 1:
The complexity of determining marker positions on non-parallel surfaces is resolved by replacing manual alignment procedures with automated optical imaging and computational triangulation. The system captures images from multiple viewing angles and uses geometric algorithms to automatically compute 3D marker positions, eliminating the need for complex manual alignment on irregular surfaces.
Solution Approach 2:
The system transitions from 2D image plane coordinates to 3D spatial coordinates through triangulation. By capturing images from multiple viewing angles (adding the temporal/dimensional dimension of multiple observations), the system can accurately determine positions of markers on non-parallel surfaces that would be impossible to measure from a single viewpoint.
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
Enables efficient and accurate determination of object marker arrangements, reducing user effort and improving tracking accuracy by using image data from multiple angles to calculate marker positions, allowing for flexible marker placement and removal of the reference device after calibration.
Implementation Method 1
The object markers may be configured to be detected optically when taking the images. As an example, the object markers may have light-reflecting or light-emitting properties
Data Source
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Figure 3A~3C
AI summary
A technique for determining an object marker arrangement comprising a plurality of object markers arranged on at least two non-parallel surfaces or non-parallel surface portions of an object is provided. The object marker arrangement is characterized by positions of the object markers, wherein a reference device with a pre-determined reference pattern is provided. A method implementation of the technique comprises several steps at least partially performed by a processing device. In more detail, the method comprises the step of receiving image data representative of a plurality of images that contain the reference pattern and at least a subset of the object markers, wherein at least some of the images were captured by an imaging device from different viewing angles. The reference pattern and the object markers were arranged in a fixed spatial relationship relative to each other when the images were captured. The method further comprises determining positions of the object markers relative to the reference pattern, wherein the position of an individual one of the object markers is determined based on at least two images that contain the individual object marker and based on geometrical information about the reference pattern.