From the course: FARO SCENE 3D Laser Scan Registration
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Noise identification and removal - Scene Tutorial
From the course: FARO SCENE 3D Laser Scan Registration
Noise identification and removal
- [Instructor] In this video, you're going to learn what noise looks like in the point cloud, how to filter it out, where and under what circumstances you may find noise in the point cloud, and why it's important to remove this extraneous data. Some hazards you may look for is when you're scanning, you may have objects that move around. Certainly don't use these as targets. That could be chairs, it could be ladders, because from one scan to another, if a condition has changed, that cloud to cloud registration may be a problem. And definitely don't put sears or targets on moveable objects. Also, noisy objects can include light fixtures, especially if they are turned on, the scan data is going to pick up all those photons and you're going to have a ton of noise around that, so I wouldn't use those as targets either. As you can see here, the yellow is the actual scan, that I've highlighted that represents all that noise. Other objects that are really dark objects or black objects…
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Contents
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Navigation controls for viewing in 2D/3D16m 5s
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Visibility settings10m 49s
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Using clipping boxes14m 11s
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Using the measurement tools10m 45s
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Noise identification and removal4m 5s
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Top-down and cloud-to-cloud registration tools15m 37s
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FARO 2018 and 2019 preprocessing with top-down and cloud-to-cloud5m 44s
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Correspondence view quality control5m 43s
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Target-based registration, part 14m 29s
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Target-based registration, part 216m 47s
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Using the Transformation tools for shift correction5m 37s
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Manually aligning X, Y, and Z shifts5m 42s
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Manually aligning tilted and angled shifts5m 26s
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Advanced registration techniques, part 125m 52s
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Advanced registration techniques, part 28m 28s
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Advanced registration techniques, part 322m 29s
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Advanced registration techniques, part 47m 41s
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Advanced registration techniques, part 527m 4s
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Advanced registration techniques, part 627m 39s
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Registration using survey data11m 51s
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