ML Anthology

Recovering and Tracking Pose of Curved 3D Objects from 2D Images

Jin-Long Chen, George C. Stockman, Kashi Rao
CVPR 1993 pp. 233-239
doi:10.1109/CVPR.1993.340984 /cvpr/1993/chen1993cvpr-recovering/

Abstract

A method of locating and tracking rigid moving objects with arbitrary curved surfaces is presented. Motion of the moving objects in a sequence of images is used to perform image segmentation and boundary extraction. The silhouette of the object model is derived by the curvature method of Basri and Ullman. The derived silhouette is then fitted to the observed silhouette to determine the object pose. Correspondence is guided by template matching, where the similarity measure is based on the minimization of the overall Euclidean distance between the derived silhouette and the observed silhouette. Bench tests and simulations confirm the viability of the approach, even when the observed silhouette is imperfect due to partial occlusion of the object or imperfect boundary extraction.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Chen et al. "Recovering and Tracking Pose of Curved 3D Objects from 2D Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.340984

Markdown

[Chen et al. "Recovering and Tracking Pose of Curved 3D Objects from 2D Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/chen1993cvpr-recovering/) doi:10.1109/CVPR.1993.340984

BibTeX

@inproceedings{chen1993cvpr-recovering,
  title     = {{Recovering and Tracking Pose of Curved 3D Objects from 2D Images}},
  author    = {Chen, Jin-Long and Stockman, George C. and Rao, Kashi},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {233-239},
  doi       = {10.1109/CVPR.1993.340984},
  url       = {https://mlanthology.org/cvpr/1993/chen1993cvpr-recovering/}
}