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Combining Laser Scans Yong Joo Kil
 

Summary: Combining Laser Scans
Yong Joo Kil
University of California, Davis
Boris Mederos
IMPA, Rio de Janairo, Brazil
Nina Amenta
University of California, Davis
Figure 1: Left, a patch of a single surface captured by a laser range scanner at about .4mm/sample. Center, we integrate many of these surfaces to create a single high-quality surface
on a higher-resolution grid. Right, a photograph of the object. Notice the improved detail on the eye and the nostril, the feather texture on the face (invisible in the low-resolution
scan), and the overall noise reduction.
We describe method for combining many copies of a surface cap-
tured with a laser range scanner to produce a single high-quality
surface. The method is inspired by the 2D image processing tech-
nique known as super-resolution [Park et al. 2003]. The input scans
are randomly shifted, so that each scan contains slightly different
information, which contributes to the final model. Noise is reduced
by averaging.
In image processing, super-resolution is based on modeling the
intensity of each low-resolution pixel as a function of the unknown
intensities of some set of high-resolution pixels (determined by

  

Source: Amenta, Nina - Department of Computer Science, University of California, Davis

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences