A Sequential Detection Framework for Feature Tracking Within Computational Constraints

Richardson, Haydn S.; Blostein, Steven D.

doi:10.1109/CVPR.1992.223238

A Sequential Detection Framework for Feature Tracking Within Computational Constraints

Haydn S. Richardson, Steven D. Blostein

CVPR 1992 pp. 861-864

doi:10.1109/CVPR.1992.223238 /cvpr/1992/richardson1992cvpr-sequential/

Abstract

A unified decision-theoretic framework for automating the establishment of feature point correspondences in a temporally dense sequence of images is discussed. The approach extends a recent sequential detection algorithm to guide the detection and tracking of object feature points through an image sequence. The resulting extended feature tracks provide robust feature correspondences, for the estimation of three-dimensional structure and motion, over an extended number of image frames.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

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Cite

Text

Richardson and Blostein. "A Sequential Detection Framework for Feature Tracking Within Computational Constraints." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992. doi:10.1109/CVPR.1992.223238

Markdown

[Richardson and Blostein. "A Sequential Detection Framework for Feature Tracking Within Computational Constraints." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1992.](https://mlanthology.org/cvpr/1992/richardson1992cvpr-sequential/) doi:10.1109/CVPR.1992.223238

BibTeX

@inproceedings{richardson1992cvpr-sequential,
  title     = {{A Sequential Detection Framework for Feature Tracking Within Computational Constraints}},
  author    = {Richardson, Haydn S. and Blostein, Steven D.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1992},
  pages     = {861-864},
  doi       = {10.1109/CVPR.1992.223238},
  url       = {https://mlanthology.org/cvpr/1992/richardson1992cvpr-sequential/}
}