ML Anthology

Making Good Features Track Better

Tiziano Tommasini, Andrea Fusiello, Emanuele Trucco, Vito Roberto
CVPR 1998 pp. 178-183
doi:10.1109/CVPR.1998.698606 /cvpr/1998/tommasini1998cvpr-making/

Abstract

This paper addresses robust feature tracking. We extend the well-known Shi-Tomasi-Kanade tracker by introducing an automatic scheme for rejecting spurious features. We employ a simple and efficient outlier rejection rule, called X84, and prove that its theoretical assumptions are satisfied in the feature tracking scenario. Experiments with real and synthetic images confirm that our algorithm makes good features track better; we show a quantitative example of the benefits introduced by the algorithm for the case of fundamental matrix estimation. The complete code of the robust tracker is available via ftp.

PDF CVPR Semantic Scholar

Cite

Text

Tommasini et al. "Making Good Features Track Better." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998. doi:10.1109/CVPR.1998.698606

Markdown

[Tommasini et al. "Making Good Features Track Better." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998.](https://mlanthology.org/cvpr/1998/tommasini1998cvpr-making/) doi:10.1109/CVPR.1998.698606

BibTeX

@inproceedings{tommasini1998cvpr-making,
  title     = {{Making Good Features Track Better}},
  author    = {Tommasini, Tiziano and Fusiello, Andrea and Trucco, Emanuele and Roberto, Vito},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1998},
  pages     = {178-183},
  doi       = {10.1109/CVPR.1998.698606},
  url       = {https://mlanthology.org/cvpr/1998/tommasini1998cvpr-making/}
}