Multi-Object Tracking with Representations of the Symmetric Group
Abstract
We present an efficient algorithm for approximately maintaining and updating a distribution over permutations matching tracks to real world objects. The algorithm hinges on two insights from the theory of harmonic analysis on noncommutative groups. The first is that most of the information in the distribution over permutations is captured by certain “low frequency” Fourier components. The second is that Bayesian updates of these components can be efficiently realized by extensions of Clausen’s FFT for the symmetric group.
Cite
Text
Kondor et al. "Multi-Object Tracking with Representations of the Symmetric Group." Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007.Markdown
[Kondor et al. "Multi-Object Tracking with Representations of the Symmetric Group." Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007.](https://mlanthology.org/aistats/2007/kondor2007aistats-multiobject/)BibTeX
@inproceedings{kondor2007aistats-multiobject,
title = {{Multi-Object Tracking with Representations of the Symmetric Group}},
author = {Kondor, Risi and Howard, Andrew and Jebara, Tony},
booktitle = {Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics},
year = {2007},
pages = {211-218},
volume = {2},
url = {https://mlanthology.org/aistats/2007/kondor2007aistats-multiobject/}
}