Using spin images for efficient object recognition in cluttered 3D scenes

Author

Johnson, Andrew E. ; Hebert, Martial

Author_Institution

Jet Propulsion Lab., Pasadena, CA, USA

Volume

21

Issue

5

fYear

1999

fDate

5/1/1999 12:00:00 AM

Firstpage

433

Lastpage

449

Abstract

We present a 3D shape-based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion. Recognition is based on matching surfaces by matching points using the spin image representation. The spin image is a data level shape descriptor that is used to match surfaces represented as surface meshes. We present a compression scheme for spin images that results in efficient multiple object recognition which we verify with results showing the simultaneous recognition of multiple objects from a library of 20 models. Furthermore, we demonstrate the robust performance of recognition in the presence of clutter and occlusion through analysis of recognition trials on 100 scenes

Keywords

data compression; image coding; image matching; image representation; object recognition; 3D shape-based object recognition system; cluttered 3D scenes; compression scheme; data level shape descriptor; efficient multiple object recognition; multiple object recognition; occlusion; point matching; spin image representation; surface matching; surface meshes; Computer vision; Image coding; Image recognition; Image representation; Layout; Libraries; Object recognition; Performance analysis; Robustness; Shape;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.765655

Filename

765655