World Academy of Science, Engineering and Technology
Published May 26, 2008 | Version 9067
Journal article Open

Clustered Signatures for Modeling and Recognizing 3D Rigid Objects

Description

This paper describes a probabilistic method for three-dimensional object recognition using a shared pool of surface signatures. This technique uses flatness, orientation, and convexity signatures that encode the surface of a free-form object into three discriminative vectors, and then creates a shared pool of data by clustering the signatures using a distance function. This method applies the Bayes-s rule for recognition process, and it is extensible to a large collection of three-dimensional objects.

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References

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