Uncertainty in interpretation of range imagery

Uncertainty in interpretation of range imagery

A description is given of a method for automatically deriving a Bayesian probability network from CAD based 3D models. This network may be used to match 3D objects to features derived from range images in the presence of uncertainty. The network describes how evidence for subparts of an object shoul...

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Bibliographische Detailangaben
1. Verfasser: Chelberg, D.M.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Assembly
Bayesian methods
Computer networks
Image segmentation
Intelligent networks
Solid modeling
Uncertainty
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Beschreibung
Zusammenfassung:A description is given of a method for automatically deriving a Bayesian probability network from CAD based 3D models. This network may be used to match 3D objects to features derived from range images in the presence of uncertainty. The network describes how evidence for subparts of an object should be combined to calculate the evidence for an object. A prototype model based range interpretation system using this method is also presented. Sample results for an object are presented. For this prototype system, sources of evidence include maximum likelihood estimate fits of circular cylinders, planes, and spheres, as well as boundary data (i.e. edges).< >
DOI:10.1109/ICCV.1990.139612