ML Anthology

The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking

Andrew Blake, Michael Isard
NeurIPS 1996 pp. 361-367
/neurips/1996/blake1996neurips-condensation/

Abstract

The power of sampling methods in Bayesian reconstruction of noisy signals is well known. The extension of sampling to temporal prob(cid:173) lems is discussed. Efficacy of sampling over time is demonstrated with visual tracking.

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Cite

Text

Blake and Isard. "The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking." Neural Information Processing Systems, 1996.

Markdown

[Blake and Isard. "The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/blake1996neurips-condensation/)

BibTeX

@inproceedings{blake1996neurips-condensation,
  title     = {{The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking}},
  author    = {Blake, Andrew and Isard, Michael},
  booktitle = {Neural Information Processing Systems},
  year      = {1996},
  pages     = {361-367},
  url       = {https://mlanthology.org/neurips/1996/blake1996neurips-condensation/}
}