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Efficient Multiple Model Recognition in Cluttered 3-D Scenes

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posted on 1998-01-01, 00:00 authored by Andrew E. Johnson, Martial Hebert
We present a 3-D 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.

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Date

1998-01-01

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    RoboticsAdaptive Agents and Intelligent Robotics

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