Extracting form features by Bayesian evidence accumulation

Michael M. Marefat, Qiang Ji, Paul J. Lever

Research output: Contribution to conferencePaper

Abstract

A novel approach based on the generation and combination of geometric and topologic evidences has been developed to identify and extract semantic features from a part solid model representation. The proposed method exploits Bayesian probabilistic propagation. It works by constructing and partitioning a graph which combines the original cavity graph representing the depression with a set of virtual links. The methods for updating these beliefs are in accordance with Bayesian probability rules.

Original languageEnglish (US)
Pages75-83
Number of pages9
StatePublished - Dec 1 1994
EventProceedings of the 1994 International Mechanical Engineering Congress and Exposition - Chicago, IL, USA
Duration: Nov 6 1994Nov 11 1994

Other

OtherProceedings of the 1994 International Mechanical Engineering Congress and Exposition
CityChicago, IL, USA
Period11/6/9411/11/94

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ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

Cite this

Marefat, M. M., Ji, Q., & Lever, P. J. (1994). Extracting form features by Bayesian evidence accumulation. 75-83. Paper presented at Proceedings of the 1994 International Mechanical Engineering Congress and Exposition, Chicago, IL, USA, .