DocumentCode :
1807873
Title :
Creating random structural descriptions of CAD models and determining object classes
Author :
Sengupta, Kuntal ; Boyer, Kim L.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
fYear :
1994
fDate :
8-11 Feb 1994
Firstpage :
38
Lastpage :
45
Abstract :
Addresses two problems related to organizing CAD models represented as random parametric structural descriptions (RPSDs). First, the authors present a method to estimate the probability information for RPSDs from CAD models. The randomness arising from viewpoint variation is captured in the random variables corresponding to the attributes of the primitives and the relationship tuples. Next, and more significantly, they present a method to subdivide a large, heterogeneous set of models into smaller, structurally homogeneous subsets based on the distribution of the eigenvalues of property matrices derived from 2½ descriptions of the CAD models. Once this is done, each sublibrary of RPSDs can be hierarchically organized
Keywords :
CAD; computational geometry; computer graphics; eigenvalues and eigenfunctions; graph theory; pattern recognition; CAD models; attributes; eigenvalues; object classes; primitives; property matrices; random parametric structural descriptions; random structural descriptions; relationship tuples; Clustering algorithms; Eigenvalues and eigenfunctions; Image sensors; Laboratories; Libraries; Object recognition; Polynomials; Random variables; Sensor phenomena and characterization; Signal analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
CAD-Based Vision Workshop, 1994., Proceedings of the 1994 Second
Conference_Location :
Champion, PA
Print_ISBN :
0-8186-5310-8
Type :
conf
DOI :
10.1109/CADVIS.1994.284518
Filename :
284518
Link To Document :
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