development of a vision-based measurement system for ... · 9/9/2014 · development of a...
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Development of a Vision-Based Measurement System for Relative Motion Compensation
Johan Lindal Haug, Morten Ottestad & Geir Hovland
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Introduction
• Motivation, about the system
• Image processing
• Computations
• Results from experiments
• Conclusion
• Q&A
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Introduction
• Why vision-based?
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Introduction
• Wave frequency 0.05 Hz to 0.125 Hz
• Accuracy: +25mm heave, +0.5° roll and pitch
• Compute all 6 DOF
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Camera model
• Frontal pinhole camera model
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Radial distortion
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Pattern
• Pattern with rounded outer corners
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Pattern
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Equipment: Initial Experiments
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Equipment: www.motion-lab.no
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Image Processing
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Image Processing - Thresholding
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Image Processing - Thresholding
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Image Processing – Region of Interest
• Assume pattern is largest dark area
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Image Processing – Feature Detection
•Harris corner detector
u-gradient v-gradient
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Image Processing – Feature Detection
•Harris corner response
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Image Processing - Feature Localization
•Binary Large OBject
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Image Processing - Feature Correspondences
Features inside pattern Features along edge
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Image Processing - Feature Correspondences
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Image Processing - Feature Correspondences
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Image Processing - Feature Correspondences
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Experiments
• Static experiments
• Dynamic experiments
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Experiments – Static results, heave
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Experiments – Static results, heave
• Raw measurements
• Calibrated measurements
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Experiments – Static results, roll
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Experiments – Static results, roll
• Raw measurements
• Calibrated measurements
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Experiments – Static results, pitch
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Experiments – Static results, pitch
• Raw measurements
• Calibrated measurements
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Experiments – Dynamic results, heave
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Experiments – Dynamic results, heave
• 0.05 Hz measurements
• 0.125 Hz measurements
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Experiments – Dynamic results, roll
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Experiments – Dynamic results, roll
• 0.05 Hz measurements
• 0.125 Hz measurements
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Experiments – Dynamic results, pitch
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Experiments – Dynamic results, pitch
• 0.05 Hz measurements
• 0.125 Hz measurements
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Experiments – Delay
• Zoomed in dynamic heave experiments
• Delay ≈ 0.1 seconds
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Conclusion
• Solution has been found
• Reduce cycletime
• Improve quality of input-data -> global shutter
• Find and eliminate pixel-noise giving variance