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10th Pacific Conference on Computer Graphics and Applications (PG'02)
Shape-Similarity Search of Three-Dimensional Models Using Parameterized Statistics
Tsinghua University, Beijing
October 09-October 11
ISBN: 0-7695-1784-6
Ryutarou Ohbuchi, Yamanashi University
Tomo Otagiri, Yamanashi University
Masatoshi Ibato, Ibaraki Computing Center, Incorporated.
Tsuyoshi Takei, Yamanashi University
In this paper, we propose a method for shape-similarity search of 3D polygonal-mesh models. The system accepts triangular meshes, but tolerates degenerated polygons, disconnected component, and other anomalies. As the feature vector, the method uses a combination of three vectors, (1) the moment of inertia, (2) the average distance of surface from the axis, and (3) the variance of distance of the surface from the axis. Values in each vector are discretely parameterized along each of the three principal axes of inertia of the model. We employed the Euclidean distance and the elastic-matching distance as the measures of distance between pairs of feature vectors. Experiments showed that the proposed shape features and distance measures perform fairly well in retrieving models having similar shape from a database of VRML models.
Index Terms:
content-based search and retrieval, geometric modeling, polygonal mesh, principal axes, elastic matching
Citation:
Ryutarou Ohbuchi, Tomo Otagiri, Masatoshi Ibato, Tsuyoshi Takei, "Shape-Similarity Search of Three-Dimensional Models Using Parameterized Statistics," pg, pp.265, 10th Pacific Conference on Computer Graphics and Applications (PG'02), 2002
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