Tracking Curvilinear Objects in 3D Space
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Solution Overview
Problem
Current systems are inadequate for accurately detecting and tracking curvilinear objects in three-dimensional spaces, particularly those that undergo significant deformations and lack stable sides, such as threads or wires, in applications like surgery and maintenance tasks.
Innovation Solution
A system comprising a video camera and data processing system that forms a computational model of the curvilinear object, using non-uniform rational B-spline models and 1D texture patterns to accurately track the object's position, orientation, and shape over time, even with large deformations, by minimizing energy through discrete optimization methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional contour tracking methods are used, then tracking of rigid structures is achieved, but tracking of deformable curvilinear objects fails
Solution Approach 1:
The patent applies dynamics by modeling the curvilinear object as a deformable structure that can change its configuration over time. The computational model includes time-varying parameters that capture the object's deformation, allowing the tracking system to adapt to dynamic shape changes while maintaining reliable tracking through continuous model updating and optimization.
2Productivity
If simple tracking algorithms are used, then computational speed is maintained, but tracking precision of curvilinear objects deteriorates
Solution Approach 1:
The patent segments the curvilinear object into discrete control points that define its shape. By representing the object as a series of controlled points rather than continuous contours, the system achieves computational efficiency through point-based tracking while maintaining precision through optimized algorithms that track each point's position and the overall object's configuration.
Solution Approach 2:
The patent employs parameter changes by using a computational model with adjustable parameters that describe the object's position, orientation, and shape. The optimization algorithm iteratively adjusts these parameters to minimize the difference between the model and observed data, achieving both computational efficiency through parameterized representation and high precision through continuous parameter optimization.
3Measurement precision
If computational models with high accuracy are used, then detection precision improves, but system complexity increases
Solution Approach 1:
The patent creates a simplified computational copy or model of the curvilinear object that captures its essential geometric properties without requiring full physical complexity. This model copy includes control points and shape parameters that represent the object's configuration, enabling accurate tracking through mathematical optimization while keeping the system complexity manageable through abstracted representation.
Data Source
AI summary
A system for detecting and tracking a curvilinear object in a three-dimensional space includes an image acquisition system including a video camera arranged to acquire a video image of the curvilinear object and output a corresponding video signal, the video image comprising a plurality n of image frames each at a respective time ti, where i=1, 2, . . . , n; and a data processing system adapted to communicate with the image acquisition system to receive the video signal. The data processing system is configured to determine a position, orientation and shape of the curvilinear object in the three-dimensional space at each time ti by forming a computational model of the curvilinear object at each time ti such that a projection of the computation model of the curvilinear object at each time ti onto a corresponding frame of the plurality of image frames of the video image matches a curvilinear image in the frame to a predetermined accuracy to thereby detect and track the curvilinear object from time t1 to time tn.