- Preservation
- Restoration
- Exhibition
- Large size
- Outdoor objects
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Digitally archive Japanese cultural heritage objects for...
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We originally proposed a method to integrate range images
into a geometric model, called Consensus Surface Algorithm
(ppt).
We have to handle large data set of range images
to model cultural heritage objects.
To accomplish this, we parallelize the merging algorithm.
Our parallel merging algorithm consists of following two methods:
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We accomplish the photometrically rigid 3D model construction in our range image integration framework. As examples of photometric attributes attached to range images, we consider two different attributes: laser reflectance strength and intensity/color. By taking consensus of photometric attributes of range images, we extract Lambertian refrectance parameter with discarding outliers such as specular refrection.
An example of merging with color: |
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The original consensus surface algorithm efficiently computes signed distances by utilizing an octree. However, it generated a mesh model in finest resolution everywhere. To reduce the amount of data to represent the object and to use computational resources efficiently, we propose a method which generates a mesh model in adaptive resolution; with appropriate resolution according to the geometric and photometric characteristics of the observed object. Our method splits an octree adaptively according to the following criteria:
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