3D object pose form clustering with multiple views

Authors:
George Stockman;Juan Carlos Esteva
Affiliations:
Michigan State University, East Lansing, MI 48824, USA;Michigan State University, East Lansing, MI 48824, USA
Venue:
Pattern Recognition Letters
Year:
1985

Citing 2
Cited 0

The use of characteristic views as a basis for recognition of three-dimensional objects

The use of characteristic views as a basis for recognition of three-dimensional objects
Matching Images to Models for Registration and Object Detection via Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence

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Abstract

A candidate pose algorithm is described which computes object pose from an assumed correspondence between a pair of 2D image points and a pair of 3D model points. By computing many pose candidates actual object pose can usually be determined by detecting a cluster in the space of all candidates. Cluster space can receive candidate pose parameters from independent computations in different camera views. It is shown that use of of geometric constraint can be sufficient for reliable pose detection, but use of other knowledge, such as edge presence and type, can be easily added for increased efficiency.