Efficient Multiple Model Recognition in Cluttered 3-D Scenes

  • Authors:
  • A. E. Johnson;M. Hebert

  • Affiliations:
  • -;-

  • Venue:
  • CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
  • Year:
  • 1998

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Abstract

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.