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Proceedings Paper

pystemlib: towards an open-source tracking, state estimation, and mapping toolbox in Python
Author(s): Emilie Altman; Peter Carniglia; Tatiana Gatsak; Bhashyam Balaji
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Paper Abstract

Python State Estimation and Modeling Library, pystemlib, is a library that implements Bayesian State Estimation theory for modeling and tracking target objects. This library was developed to overcome the limitations associated with licensed programming languages as well as imperative and numerical matrix-based programming styles that were used in previously developed libraries. pystemlib incorporates object-oriented, functional, and symbolic programming to develop accurate and easy-to-use tracking filters and models. This library is also capable of mapping state estimation results onto the geographical areas to which they correspond. Future work on this library will include optimizing the algorithms for speed and extending the library to incorporate multi-target tracking, data fusion, and image and video processing.

Paper Details

Date Published: 27 April 2018
PDF: 12 pages
Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 106460K (27 April 2018); doi: 10.1117/12.2303767
Show Author Affiliations
Emilie Altman, Defence Research and Development Canada (Canada)
Queen's Univ. (Canada)
Peter Carniglia, Defence Research and Development Canada (Canada)
Queen's Univ. (Canada)
Tatiana Gatsak, Defence Research and Development Canada (Canada)
Univ. of Waterloo (Canada)
Bhashyam Balaji, Defence Research and Development Canada (Canada)


Published in SPIE Proceedings Vol. 10646:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII
Ivan Kadar, Editor(s)

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