3D object recognition by indexing structural invariants from multiple views

R. Mohan*, D. Weinshall, R. R. Sarukkai

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

We present a method for 3D object recognition from 2D image sequences. The system uses feature points tracked over three or more views to compute structural invariants, which serve as 3D shape representations. Object recognition is performed by using these Euclidean invariants as indices into a high-dimensional shape table. The use of indexing obliviates any need for matching models to images. In addition, the representation of 3D objects is extracted from 2D views, eliminating the cumbersome burden of having to obtain 3D models. The proposed scheme was implemented using a mixed database of real and simulated objects. We present experiments that show good recognition results on real objects and simulated objects corrupted with noise.

Original languageAmerican English
Title of host publication1993 IEEE 4th International Conference on Computer Vision
PublisherPubl by IEEE
Pages264-268
Number of pages5
ISBN (Print)0818638729
StatePublished - 1993
Externally publishedYes
Event1993 IEEE 4th International Conference on Computer Vision - Berlin, Ger
Duration: 11 May 199314 May 1993

Publication series

Name1993 IEEE 4th International Conference on Computer Vision

Conference

Conference1993 IEEE 4th International Conference on Computer Vision
CityBerlin, Ger
Period11/05/9314/05/93

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