Efficient Multiple Model Recognition in Cluttered 3-D Scenes

Johnson, Andrew E.; Hebert, Martial

doi:10.1109/CVPR.1998.698676

Efficient Multiple Model Recognition in Cluttered 3-D Scenes

Andrew E. Johnson, Martial Hebert

CVPR 1998 pp. 671-677

doi:10.1109/CVPR.1998.698676 /cvpr/1998/johnson1998cvpr-efficient/

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.

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Text

Johnson and Hebert. "Efficient Multiple Model Recognition in Cluttered 3-D Scenes." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998. doi:10.1109/CVPR.1998.698676

Markdown

[Johnson and Hebert. "Efficient Multiple Model Recognition in Cluttered 3-D Scenes." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998.](https://mlanthology.org/cvpr/1998/johnson1998cvpr-efficient/) doi:10.1109/CVPR.1998.698676

BibTeX

@inproceedings{johnson1998cvpr-efficient,
  title     = {{Efficient Multiple Model Recognition in Cluttered 3-D Scenes}},
  author    = {Johnson, Andrew E. and Hebert, Martial},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1998},
  pages     = {671-677},
  doi       = {10.1109/CVPR.1998.698676},
  url       = {https://mlanthology.org/cvpr/1998/johnson1998cvpr-efficient/}
}