Projector Calibration Using Vision-Based Homography
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Solution Overview
Problem
Existing computer systems with projectors struggle to automatically align projected images onto touch mats without user intervention, leading to wasted space and overextension of images, which affects the usability of the touch mat as a secondary display area.
Innovation Solution
A vision-based calibration technique using a projector, camera, and processor to align the projection area with the touch mat by projecting white light in specific geometric configurations, calculating homography matrices, and adjusting the projector's parameters to ensure accurate alignment of the image within the touch mat boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual alignment method is used, then alignment accuracy can be achieved, but user intervention is required and calibration time increases
Solution Approach 1:
The system performs self-calibration by automatically detecting the touch mat boundaries and calculating transformation parameters without user intervention. The projector and camera work together to autonomously align the projection area with the touch mat, eliminating the need for manual alignment while maintaining high precision.
Solution Approach 2:
The manual mechanical alignment process is replaced with an automated vision-based system. The camera captures images of the touch mat, and the processor automatically calculates the geometric transformation parameters, substituting the manual mechanical adjustment with an automated optical and computational system.
2Area of stationary object
If projection area is extended to cover entire touch mat, then coverage area increases, but image overextension occurs beyond touch mat boundaries
Solution Approach 1:
The system dynamically adjusts the projection parameters based on the detected touch mat boundaries. By calculating the geometric transformation parameters from the captured images, the projector adapts its projection area to precisely match the touch mat dimensions, achieving full coverage without overextension.
Solution Approach 2:
The camera captures the actual projection area and touch mat boundaries, providing feedback to the processor. The processor uses this feedback to calculate accurate transformation parameters and adjust the projection, ensuring the projected image perfectly matches the touch mat area without extending beyond boundaries.
3Loss of time
If automated calibration is implemented, then calibration time decreases, but system complexity increases
Solution Approach 1:
The camera serves multiple functions: it captures the touch mat boundaries for calibration and can also capture projected images for verification. The processor performs both image processing and geometric transformation calculations. This multi-functionality reduces the need for additional dedicated components, managing system complexity while enabling automated calibration.
4Adaptability or versatility
If touch mat is used as secondary display area, then display versatility increases, but image alignment accuracy deteriorates
Solution Approach 1:
The system performs preliminary calibration by detecting the touch mat boundaries and calculating transformation parameters before projecting the actual display content. This preliminary alignment ensures that subsequent projections are accurately positioned on the touch mat, maintaining high alignment accuracy while enabling versatile display usage.
Data Source
AI summary
An example calibration device includes a projector projecting a first light region including a first area onto and extending over a border of a non-patterned touch mat. A camera captures a first image of the first light region. A processor establishes a first set of four corner coordinates of the touch mat. The projector projects a second light region including a second area onto the touch mat. The second area is smaller than the first area. The camera captures a second image of the second light region. The processor performs a perspective transformation of the second image using the first set of corner coordinates and a resolution of the second light region to get a second set of four corner coordinates of the touch mat in a coordinate plane of the projector. The processor aligns the first and second set of four corner coordinates.