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1998
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Efficient Multiple Model Recognition in Cluttered 3-D Scenes

10 years 13 days ago
Efficient Multiple Model Recognition in Cluttered 3-D Scenes
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 sugaces 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 su$ace meshes. We present a compression scheme for spinimages that results in eficient 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.
Andrew Edie Johnson, Martial Hebert
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 1998
Where CVPR
Authors Andrew Edie Johnson, Martial Hebert
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