An evidential reasoning approach for recognizing shape features

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

This paper introduces an evidential reasoning based approachfor recognizing and extracting manufacturing featuresfrom solid model descriptionof objects. A major dificultyfaced by previouslyproposed methodsforfeature extraction has been the interaction betweenfeatures. In interacting situations, the representation for various primitivefeatures is non-unique,making their recognition very difficult. We develop an approach based on generating and combining geometric and topological evidencesfor recognizing interactingfeatures. The essence of our approach is in finding a set of correct and necessary virtual links throughaggregating the available geometric and topologic evidences at different abstraction levels. The identifed virtual links are then augmented to the cavity graphrepresenting a depression of an object so that the resulting supergraph can be partitioned to obtain the features of the object. The main contributions of our approach include introducing the evidential reasoning (Dempster-Shafer theory) to the feature extraction domain and developing the theory of principle of association to overcome the mutual exclusivenessassumption of the Dempster-Shafertheory.

Original languageEnglish (US)
Title of host publicationProceedings the 11th Conference on Artificial Intelligence for Applications, CAIA 1995
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages162-168
Number of pages7
ISBN (Electronic)0818670703, 9780818670701
DOIs
StatePublished - Jan 1 1995
Event11th Conference on Artificial Intelligence for Applications, CAIA 1995 - Los Angeles, United States
Duration: Feb 20 1995Feb 23 1995

Publication series

NameProceedings the 11th Conference on Artificial Intelligence for Applications, CAIA 1995

Conference

Conference11th Conference on Artificial Intelligence for Applications, CAIA 1995
CountryUnited States
CityLos Angeles
Period2/20/952/23/95

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Science Applications

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    Ji, Q., Marefat, M. M., & Lever, P. J. (1995). An evidential reasoning approach for recognizing shape features. In Proceedings the 11th Conference on Artificial Intelligence for Applications, CAIA 1995 (pp. 162-168). [378776] (Proceedings the 11th Conference on Artificial Intelligence for Applications, CAIA 1995). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAIA.1995.378776