NDLI: Shape-similarity search of three-dimensional models using parameterized statistics

Content Provider	IEEE Xplore Digital Library
Author	Ohbuchi, R. Otagiri, T. Ibato, M. Takei, T.
Copyright Year	2002
Description	Author affiliation: Comput. Sci. Dept., Yamanashi Univ., Japan (Ohbuchi, R.; Otagiri, T.)
Abstract	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.
Starting Page	265
Ending Page	274
File Size	1933021
Page Count	10
File Format	PDF
ISBN	0769517846
DOI	10.1109/PCCGA.2002.1167870
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-10-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Statistics Solid modeling Content based retrieval Shape measurement Image converters Information retrieval Computer science Euclidean distance Performance evaluation Spatial databases
Content Type	Text
Resource Type	Article

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