ML Anthology

Eigenshapes for 3D Object Recognition in Range Data

Richard J. Campbell, Patrick J. Flynn
CVPR 1999 pp. 2505-2510
doi:10.1109/CVPR.1999.784728 /cvpr/1999/campbell1999cvpr-eigenshapes/

Abstract

Much of the recent research in object recognition has adopted an appearance-based scheme, wherein objects to be recognized are represented as a collection of prototypes in a multidimensional space spanned by a number of characteristic vectors (eigen-images) obtained from training views. In this paper, we extend the appearance-based recognition scheme to handle range (shape) data. The result of training is a set of 'eigensurfaces' that capture the gross shape of the objects. These techniques are used to form a system that recognizes objects under an arbitrary rotational pose transformation. The system has been tested on a 20 object database including free-form objects and a 54 object database of manufactured parts. Experiments with the system point out advantages and also highlight challenges that must be studied in future research.

CVPR Semantic Scholar

Cite

Text

Campbell and Flynn. "Eigenshapes for 3D Object Recognition in Range Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1999. doi:10.1109/CVPR.1999.784728

Markdown

[Campbell and Flynn. "Eigenshapes for 3D Object Recognition in Range Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1999.](https://mlanthology.org/cvpr/1999/campbell1999cvpr-eigenshapes/) doi:10.1109/CVPR.1999.784728

BibTeX

@inproceedings{campbell1999cvpr-eigenshapes,
  title     = {{Eigenshapes for 3D Object Recognition in Range Data}},
  author    = {Campbell, Richard J. and Flynn, Patrick J.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1999},
  pages     = {2505-2510},
  doi       = {10.1109/CVPR.1999.784728},
  url       = {https://mlanthology.org/cvpr/1999/campbell1999cvpr-eigenshapes/}
}