3 October 1995 Issues for data reduction of dense three-dimensional data
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Acquiring a large quantity of 3D data has become common plane with the advent of new technologies. Reducing the number of data points improves processing speed and storage requirements. Astute data reduction requires an understanding of the correlation between data measures and geometric measures. These relationships are dependent upon the data reduction algorithm used. This paper investigates these relationships for a small number of data reduction algorithms. A framework is presented for tracking these changes and for assisting a user in identifying the most appropriate data reduction method for their application.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joseph H. Nurre, Joseph H. Nurre, Jennifer J. Whitestone, Jennifer J. Whitestone, Dennis B. Burnsides, Dennis B. Burnsides, David M. Hoeferlin, David M. Hoeferlin, } "Issues for data reduction of dense three-dimensional data", Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222715; https://doi.org/10.1117/12.222715

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