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Highlighting Feature Regions Combined with See-Through Visualization of Laser-Scanned Cultural Heritage

conferencePaper

DOI:10.1109/Culture.and.Computing.2017.18
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Authors: Okamoto Naoya / Hasegawa Kyoko / Li Liang / Okamoto Atsushi / Tanaka Satoshi

Extracted Abstract:

—We propose a method for precise point-based see- through visualization in which feature regions are highlighted. And by using this method we can recognize the 3D structures of the cultural heritage clearly. The recent rapid development of laser scanners has enabled the precise measurement of real cultural heritage objects. In the measurement, we acquire a point cloud consisting of a large scale of 3D points. The point cloud records complex outer and inner 3D structures of the measured object. See-through visualization is an effective method for recognizing inner 3D structures. To recognize the entire 3D structures based on the point cloud, we need a method for extracting and visualizing feature regions recorded in the point cloud. Therefore we combined these two methods to obtain the highly visible 3D structures of cultural heritage objects. Keywords—laser-scanned point cloud; cultural heritage; principal component analysis; see-through visualization I.

Level 1: Include/Exclude

  • Papers must discuss situated information visualization* (by Willet et al.) in the application domain of CH.
    *A situated data representation is a data representation whose physical presentation is located close to the data’s physical referent(s).
    *A situated visualization is a situated data representation for which the presentation is purely visual – and is typically displayed on a screen.
  • Representation must include abstract data (e.g., metadata).
  • Papers focused solely on digital reconstruction without information visualization aspects are excluded.
  • Posters and workshop papers are excluded to focus on mature research contributions.
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