Automatic Calibration of Image Devices for Projection Mapping
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Solution Overview
Problem
The process of projection mapping is complex due to the need for precise calibration of projectors relative to three-dimensional objects, which is often manual and time-consuming, requiring technician intervention, especially when cameras or projectors move, leading to temporary system shutdowns when technicians are unavailable.
Innovation Solution
A system and method for automatic calibration of image devices, using a computing device to determine the pose of projectors and cameras relative to a physical object by projecting structured light patterns and calculating pixel correspondences, allowing for automatic determination of relative locations and orientations, eliminating the need for manual calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration procedure is used to determine camera poses, then calibration accuracy can be achieved, but the process becomes time-consuming and requires technician intervention
Solution Approach 1:
The system performs self-calibration by automatically determining camera poses through image processing and coordinate calculations without requiring technician intervention. The computer executes algorithms to process images from multiple cameras, calculate pixel correspondences, and determine camera poses autonomously, making the system self-sufficient for calibration tasks.
Solution Approach 2:
The patent replaces manual mechanical calibration procedures with an automated computational system. Instead of technicians physically adjusting and measuring camera positions, the system uses image processing algorithms, coordinate transformations, and automated calculations to determine camera poses, substituting mechanical/manual operations with computational automation.
2Reliability
If technician intervention is required for calibration, then accurate pose determination is achieved, but the system must be shut down temporarily when technicians are unavailable
Solution Approach 1:
The calibration system operates autonomously without requiring technician presence. The computer automatically processes images, calculates pixel correspondences, determines camera poses, and updates projection mappings, enabling the system to maintain continuous operation and high availability while simplifying the operational process.
Solution Approach 2:
The automated calibration system enables continuous operation of the projection mapping system. By eliminating the need for technician intervention and temporary shutdowns, the system can perform calibration tasks continuously and automatically, ensuring uninterrupted operation and maintaining projection accuracy over time.
3Measurement precision
If cameras are used to calibrate projector locations, then pose determination is achieved, but the camera poses themselves must be known and calibrated first
Solution Approach 1:
The system simultaneously determines both camera poses and projector poses through a unified automated calibration process. The computer processes images from multiple cameras, calculates pixel correspondences between cameras and projectors, and determines all poses autonomously without requiring pre-calibrated cameras, making the entire calibration process self-sufficient.
Solution Approach 2:
The calibration system performs multiple functions simultaneously: it calibrates camera poses, determines projector poses, and establishes coordinate transformations between different devices. This multi-functional approach eliminates the need for separate calibration steps and reduces overall system complexity while maintaining measurement precision.
Data Source
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AI summary
A device, system and method for automatic calibration of image devices is provided. Triplets of at least three image devices, including a projector, are in non-collinear arrangements, and pairs of the image devices have overlapping fields of view on a physical object. Pixel correspondences between the pairs are used to determine relative vectors between the image devices. Relative locations between each of the image devices are determined based on the relative vectors with a relative distance between one pair of the image devices is to an arbitrary distance, the relative locations being further relative to a cloud-of-points representing the object. A model of the object and the cloud-of-points are aligned to transform the relative locations of each of the image devices to locations relative to the model. The projector is controlled to project onto the object based at least on the locations relative to the model.