Calibration System Using Marker Array for Motion Tracking
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Solution Overview
Problem
Calibration of motion tracking subsystems in imaging-based dimensioning systems for detecting moving objects is time-consuming and computationally demanding.
Innovation Solution
A calibration system using a reference device with an array of markers, a camera, and a computing device to generate calibration data by mapping camera frame coordinates to capture volume frame coordinates, enabling accurate tracking of moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods are used for motion tracking subsystems, then measurement precision is achieved, but calibration time and computational complexity increase significantly
Solution Approach 1:
The calibration device is divided into multiple independent markers distributed across the capture volume. Each marker provides independent calibration information, allowing the system to process calibration data in parallel and reduce overall computational complexity while maintaining precision through the distributed measurement approach.
Solution Approach 2:
The patent introduces a spatial distribution dimension by placing markers throughout the three-dimensional capture volume rather than using traditional two-dimensional calibration patterns. This spatial distribution enables parallel processing across multiple depth planes, significantly reducing calibration time while preserving measurement precision through volumetric coverage.
2Measurement precision
If traditional calibration methods are used for motion tracking subsystems, then measurement precision is achieved, but computational complexity increases significantly
Solution Approach 1:
The calibration computation is segmented into independent marker processing units. Each marker's position and orientation are processed independently, allowing parallel computation across multiple CPU cores or GPUs. This segmentation dramatically reduces the computational complexity burden on any single processing unit while maintaining overall calibration precision.
Solution Approach 2:
The patent uses multiple identical marker templates that can be recognized through template matching or feature detection. This copying approach allows the system to use simple, efficient pattern recognition algorithms rather than complex calibration computations, reducing overall computational complexity while achieving precise calibration through the replicated marker structure.
3Reliability
If calibration is performed accurately, then tracking accuracy is improved, but the time required for calibration increases
Solution Approach 1:
The calibration device is pre-configured with markers at known positions and orientations before use. This preliminary setup eliminates the need for complex real-time calibration computations during tracking operations. The pre-computed calibration parameters can be stored and applied directly, maintaining tracking accuracy while significantly improving calibration efficiency and reducing time requirements.
Solution Approach 2:
The calibration device is designed to be self-calibrating through its distributed marker structure. The markers automatically provide calibration information when captured by the imaging system, eliminating the need for manual calibration procedures or complex computational algorithms. This self-service approach maintains accuracy while dramatically improving calibration efficiency.
Data Source
AI summary
A calibration system includes: a reference device including an array of markers at predetermined positions; a camera; and a computing device configured to: store reference data defining the predetermined positions of the markers in a capture volume frame of reference; obtain a calibration image of the reference device captured by the camera; detect image positions of the markers in the calibration image, the image positions defined according to camera frame of reference; based on the image positions of the markers and the reference data, generate calibration data mapping coordinates in the camera frame of reference to coordinates in the capture volume frame of reference.