The document discusses 2-D and 3-D information processing, emphasizing the use of cameras and scanners to capture raw data in the form of pixels and point clouds. It highlights the instabilities of edgels and surfels as boundary points and advocates for fitting stable 2-D curves and 3-D surfaces to these elements to derive more reliable information. The author encourages further discussion on the topic.

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Dr.-Ing. Sung Joon Ahn
CurvSurf, Inc.
Some Thoughts on
2-D/3-D Information Processing

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Information 2-D Camera 3-D Camera 3-D CT-Scanner
Primary Pixel Surfel Voxel
Secondary Edgel Surface Surfel
Tertiary 2-D Curve 3-D Curve Surface
Quaternary 2-D Point 3-D Point 3-D Curve
Quinary -- -- 3-D Point
2-D/3-D Information Unit

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Description 2-D Camera 3-D CT-Scanner
Sensor raw data Pixel Voxel
Boundary point of regions Edgel Surfel
Mathematical
representation
2-D Curve Surface
Intersection 2-D Point 3-D Curve
Corner -- 3-D Point
2-D/3-D Information Description
* With 3-D Camera:
Sensor raw data ( = point cloud, surfels ) = Boundary points of 3-D volumes.

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• Pixels are the sensor raw data.
• Edgels are boundary points of regions
and are unstable information.
• Edgels do not much provide information
on regions.
• 2-D curves fitted to edgels represent
mathematically the boundary of regions.
They are relatively stable information
because of average-effect.
• Position, rotation, size, corner, etc. can
be deduced from the 2-D curves fitted.
2-D Information Processing

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• Point cloud (surfels) is the sensor raw data.
• Surfels are boundary points of volumes
and are unstable information.
• Surfels do not much provide information
on volumes.
• Surfaces fitted to surfels represent
mathematically the boundary of volumes.
They are relatively stable information
because of average-effect.
• Position, rotation, size, edge, corner, etc.
can be deduced from the surfaces fitted.
3-D Information Processing (1)

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• Some people are trying to extract more
unstable edgels from unstable point cloud,
ignoring the richness of point cloud.
• Much better is to fit stable surfaces to
unstable point cloud and deduce
more stable information of position,
rotation, size, etc. from the surfaces fitted.
3-D Information Processing (2)
+ + =

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• Further discussions are welcomed
• https://plus.google.com/+CurvSurf
Closing
Thank you!