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Efficient multiple model recognition in cluttered 3-D scenes

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2 Author(s)
A. E. Johnson ; Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA ; M. 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

Published in:

Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on

Date of Conference:

23-25 Jun 1998