3D Acquisition System Calibration via Epipolar Geometry
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Solution Overview
Problem
Existing three-dimensional (3D) acquisition systems face calibration challenges due to external factors like temperature, humidity, and displacement of sensing and projecting devices, which often require manual recalibration using calibration objects and may not be performed promptly or accurately.
Innovation Solution
An optoelectronic assembly that includes a 3D scanner, a projector unit, and multiple cameras, with a controller using epipolar geometry and distortion compensation techniques to dynamically calibrate and correct distortions caused by external factors, allowing for automatic adjustment of projection angles and image alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual recalibration is performed using calibration objects, then measurement precision is improved, but loss of time increases and ease of operation deteriorates
Solution Approach 1:
The system performs automatic self-calibration by capturing images of the calibration object with multiple cameras, computing 3D coordinates through stereoscopic vision, and automatically updating calibration parameters without requiring manual intervention. The processor autonomously completes the entire calibration process from image capture to parameter correction.
Solution Approach 2:
The patent replaces manual mechanical calibration operations with an automated optical-computational system. Instead of physically adjusting components by hand, the system uses cameras to capture images and a processor to compute calibration parameters automatically, substituting mechanical adjustment with digital computation.
2Measurement precision
If manual recalibration is performed using calibration objects, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The calibration object serves multiple functions: it provides known 3D coordinates for calibration, acts as a reference for stereoscopic image matching, and enables verification of calibration accuracy. The same object is used for both calibration and validation purposes, reducing the need for separate specialized components.
Solution Approach 2:
The system creates a digital 3D model (copy) of the calibration object through stereoscopic vision by capturing images with multiple cameras and computing spatial coordinates. This digital representation is then used for calibration calculations, replacing the need for direct physical measurement and simplifying the calibration process.
3Device complexity
If calibration is performed at assembly time only, then device complexity is reduced, but reliability deteriorates due to deviations from external factors
Solution Approach 1:
The system transitions from static calibration (performed once at assembly) to dynamic calibration (performed automatically when needed during operation). The calibration process can be re-executed at any time to adapt to changing environmental conditions, making the system flexible and responsive rather than fixed and rigid.
Solution Approach 2:
The system implements a feedback mechanism where calibration accuracy is continuously monitored and can be re-calibrated automatically when deviations are detected. The processor compares measured coordinates with expected coordinates and triggers recalibration when accuracy thresholds are not met, creating a closed-loop control system that maintains reliability.
Data Source
AI summary
Embodiments of the present disclosure provide techniques and configurations for an optoelectronic three-dimensional object acquisition assembly configured to correct image distortions. In one instance, the assembly may comprise a first device configured to project a light pattern on an object at a determined angle; a second device configured to capture a first image of the object illuminated with the projected light pattern; a third device configured to capture a second image of the object; and a controller coupled to the first, second, and third devices and configured to reconstruct an image of the object from geometric parameters of the object obtained from the first image, and to correct distortions in the reconstructed image caused by a variation of the determined angle of the light pattern projection, based at least in part on the first and second images of the object. Other embodiments may be described and/or claimed.