Projection Marker Detection for Accurate Multi-Projector Alignment
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Solution Overview
Problem
Existing projection systems face challenges in accurately adjusting the projection position due to obstacles and uneven surfaces, leading to incomplete detection of markers used for alignment.
Innovation Solution
A control device and method that projects multiple markers of different colors, performs initial detection, and employs subtraction processes on captured image data to identify undetected markers, adjusting projection positions based on detected markers to ensure accurate alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single detection process is used to detect markers, then the detection process is simple and fast, but markers obscured by obstacles or on uneven surfaces cannot be detected
Solution Approach 1:
The detection process is segmented into multiple independent detection processes, each using different detection conditions (different colors, different positions, different imaging conditions). This allows the system to detect markers that may be obscured in one detection process by using other detection processes, thereby improving marker detection completeness without requiring a single complex detection algorithm.
Solution Approach 2:
The system performs multiple detection processes beyond what a single detection would provide. By conducting repeated detections with varying conditions (different colors, positions, imaging parameters), the system ensures that even if some markers are missed in one detection, they can be detected in subsequent detections, achieving excessive action to guarantee complete marker detection.
2Measurement precision
If markers are detected using standard image processing, then the process is straightforward, but markers obscured by obstacles or blending with background cannot be distinguished
Solution Approach 1:
Different regions of the projection surface are detected using locally optimized detection conditions. The system divides the detection area and applies appropriate detection parameters (colors, imaging conditions) based on local characteristics, allowing markers in different regions to be detected effectively even when obstacles or background patterns vary locally.
Solution Approach 2:
The system utilizes multiple colors for markers and performs detection processes tailored to each color. By detecting markers in different color channels and combining results, the system can distinguish markers from backgrounds that may blend with certain colors, improving marker distinguishability through multi-color detection strategies.
3Manufacturing precision
If projection position adjustment is performed without detecting all markers, then the adjustment process is fast, but the alignment accuracy is compromised
Solution Approach 1:
The system performs preliminary detection actions by conducting multiple detection processes before final projection position adjustment. By detecting markers under various conditions in advance and compiling detection results, the system ensures complete marker detection before calculation, improving alignment accuracy without significantly extending the overall adjustment time.
Solution Approach 2:
The system uses feedback from multiple detection processes to iteratively improve marker detection completeness. Detection results from each process feed into the next, allowing the system to identify undetected markers and adjust detection parameters accordingly, ensuring all markers are detected before final alignment calculation, thereby guaranteeing projection alignment accuracy.
Data Source
AI summary
A control device includes a processor. The processor is configured to instruct a projection device to project a first image including a plurality of markers for adjusting a projection position, perform a first detection process of detecting the plurality of markers based on first captured image data that is obtained by capturing a projection image of the first image, and perform a second detection process of detecting, in a case where there is an undetected marker that is not detected in the first detection process, at least the undetected marker.