View Item 

Performance Evaluation for Large-Scale Multi-Target Tracking Algorithms

Access Status
Fulltext not available
Authors
Date
2018
Type
Conference Paper

Metadata
Show full item record
Citation
Beard, M. and Vo, B.T. and Vo, B. 2018. Performance Evaluation for Large-Scale Multi-Target Tracking Algorithms, pp. 1575-1581.
Source Title
2018 21st International Conference on Information Fusion, FUSION 2018
DOI
ISBN
School
School of Electrical Engineering, Computing and Mathematical Science (EECMS)
URI
Collection
Abstract

© 2018 ISIF The traditional method of applying the optimal subpattern assignment (OSPA) metric cannot fully evaluate multitarget tracking performance, as it does not account for phenomena such as track label switching, and track fragmentation. The OSPA(2)has been proposed as a technique for applying the OSPA distance in a way that captures these effects, while retaining the properties of a true metric. In this paper, we demonstrate the behaviour of the OSPA(2)on some numerical examples, discuss some of its advantages and limitations, and show that it is capable of being applied to performance evaluation of large-scale scenarios in the order of a thousand targets.