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Reducing Drift in Parametric Motion Tracking

Ali Rahimi, Louis-Philippe Morency, Trevor Darrell
ICCV 2001 pp. 315-322
doi:10.1109/ICCV.2001.10012 /iccv/2001/rahimi2001iccv-reducing/

Abstract

We develop a class of differential motion trackers that automatically stabilize when in finite domains. Most differential trackers compute motion only relative to one previous frame, accumulating errors indefinitely. We estimate pose changes between a set of past frames, and develop a probabilistic framework for integrating those estimates. We use an approximation to the posterior distribution of pose changes as an uncertainty model for parametric motion in order to help arbitrate the use of multiple base frames. We demonstrate this framework on a simple 2D translational tracker and a 3D, 6-degree of freedom tracker.

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Cite

Text

Rahimi et al. "Reducing Drift in Parametric Motion Tracking." IEEE/CVF International Conference on Computer Vision, 2001. doi:10.1109/ICCV.2001.10012

Markdown

[Rahimi et al. "Reducing Drift in Parametric Motion Tracking." IEEE/CVF International Conference on Computer Vision, 2001.](https://mlanthology.org/iccv/2001/rahimi2001iccv-reducing/) doi:10.1109/ICCV.2001.10012

BibTeX

@inproceedings{rahimi2001iccv-reducing,
  title     = {{Reducing Drift in Parametric Motion Tracking}},
  author    = {Rahimi, Ali and Morency, Louis-Philippe and Darrell, Trevor},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2001},
  pages     = {315-322},
  doi       = {10.1109/ICCV.2001.10012},
  url       = {https://mlanthology.org/iccv/2001/rahimi2001iccv-reducing/}
}