Recognizing objects in range images and finding their position in space

Jun Ohya, Daniel DeMenthon, Larry S. Davis

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

1 Citation (Scopus)

Abstract

We present a method for recognizing polyhedral objects from range images. An object is said to be recognized as one of the models of a library of object models when many features of the model can be made to match the features of the observed object by the same rotation-translation transformation (the object pose). In the proposed approach, the number of considered pairs of image and model features is reduced by selecting at random only a few of all the possible image features and matching them to appropriate model features. The rotation and translation required for each match are computed, and a robust LMS (Least Median of Squares) method is applied to determine clusters in translation and rotation spaces. The validity of the object pose suggested by the clusters is verified by a similarity measure which evaluates how well a model in the suggested pose would fit the original range image. The pose estimation and verification are performed for all models in the model library. The recognized model is the model which yields the smallest value of the similarity measure, and the pose of the object is found in the process.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems
Editors Anon
Place of PublicationNew York, NY, United States
PublisherPubl by ACM
Pages252-257
Number of pages6
ISBN (Print)0897913728
Publication statusPublished - 1991
Externally publishedYes
EventProceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems - IEA/AIE 90 - Charleston, SC, USA
Duration: 1990 Jul 151990 Jul 18

Other

OtherProceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems - IEA/AIE 90
CityCharleston, SC, USA
Period90/7/1590/7/18

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Ohya, J., DeMenthon, D., & Davis, L. S. (1991). Recognizing objects in range images and finding their position in space. In Anon (Ed.), Proceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (pp. 252-257). New York, NY, United States: Publ by ACM.

Recognizing objects in range images and finding their position in space. / Ohya, Jun; DeMenthon, Daniel; Davis, Larry S.

Proceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. ed. / Anon. New York, NY, United States : Publ by ACM, 1991. p. 252-257.

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

Ohya, J, DeMenthon, D & Davis, LS 1991, Recognizing objects in range images and finding their position in space. in Anon (ed.), Proceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. Publ by ACM, New York, NY, United States, pp. 252-257, Proceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems - IEA/AIE 90, Charleston, SC, USA, 90/7/15.
Ohya J, DeMenthon D, Davis LS. Recognizing objects in range images and finding their position in space. In Anon, editor, Proceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. New York, NY, United States: Publ by ACM. 1991. p. 252-257
Ohya, Jun ; DeMenthon, Daniel ; Davis, Larry S. / Recognizing objects in range images and finding their position in space. Proceedings of the 3rd International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. editor / Anon. New York, NY, United States : Publ by ACM, 1991. pp. 252-257
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