Extracting form features by Bayesian evidence accumulation

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

Extracting form features by Bayesian evidence accumulation

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

Electrical and Computer Engineering

Research output: Contribution to conference › Paper › peer-review

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 language	English (US)
Pages	75-83
Number of pages	9
State	Published - 1994
Event	Proceedings of the 1994 International Mechanical Engineering Congress and Exposition - Chicago, IL, USA Duration: Nov 6 1994 → Nov 11 1994

Other

Other	Proceedings of the 1994 International Mechanical Engineering Congress and Exposition
City	Chicago, IL, USA
Period	11/6/94 → 11/11/94

ASJC Scopus subject areas

Industrial and Manufacturing Engineering
Mechanical Engineering

Cite this

@conference{405ab8d1fa0b4b9d8c7b882b1d0274ce,

title = "Extracting form features by Bayesian evidence accumulation",

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.",

author = "Marefat, {Michael M.} and Qiang Ji and Lever, {Paul J.}",

year = "1994",

language = "English (US)",

pages = "75--83",

note = "Proceedings of the 1994 International Mechanical Engineering Congress and Exposition ; Conference date: 06-11-1994 Through 11-11-1994",

}

TY - CONF

T1 - Extracting form features by Bayesian evidence accumulation

AU - Marefat, Michael M.

AU - Ji, Qiang

AU - Lever, Paul J.

PY - 1994

Y1 - 1994

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0028757691&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0028757691&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0028757691

SP - 75

EP - 83

T2 - Proceedings of the 1994 International Mechanical Engineering Congress and Exposition

Y2 - 6 November 1994 through 11 November 1994

ER -

Extracting form features by Bayesian evidence accumulation

Abstract

Other

ASJC Scopus subject areas

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Cite this