The Information-Form Data Association Filter
Abstract
This paper presents a new filter for online data association problems in high-dimensional spaces. The key innovation is a representation of the data association posterior in information form, in which the “proxim- ity” of objects and tracks are expressed by numerical links. Updating these links requires linear time, compared to exponential time required for computing the exact posterior probabilities. The paper derives the algorithm formally and provides comparative results using data obtained by a real-world camera array and by a large-scale sensor network simu- lation.
Cite
Text
Schumitsch et al. "The Information-Form Data Association Filter." Neural Information Processing Systems, 2005.Markdown
[Schumitsch et al. "The Information-Form Data Association Filter." Neural Information Processing Systems, 2005.](https://mlanthology.org/neurips/2005/schumitsch2005neurips-informationform/)BibTeX
@inproceedings{schumitsch2005neurips-informationform,
title = {{The Information-Form Data Association Filter}},
author = {Schumitsch, Brad and Thrun, Sebastian and Bradski, Gary and Olukotun, Kunle},
booktitle = {Neural Information Processing Systems},
year = {2005},
pages = {1193-1200},
url = {https://mlanthology.org/neurips/2005/schumitsch2005neurips-informationform/}
}