Performance evaluation of multi-target tracking using the OSPA metric

Performance evaluation of multi-target tracking algorithms is of great practical importance in the design and comparison of tracking systems. Recently a consistent metric for performance evaluation of multi-object filters (referred to as OSPA metric) has been proposed. In this paper we describe how the OSPA metric can be adapted to evaluate the performance of multi-target tracking algorithms. The main idea is to introduce the track label error into consideration in order to capture the data association performance, in addition to the existing cardinality and localisation errors. The paper demonstrates the proposed method by assessing and comparing the performance of two particle filters for multi-target tracking.

[1]  Ba-Ngu Vo,et al.  A Consistent Metric for Performance Evaluation of Multi-Object Filters , 2008, IEEE Transactions on Signal Processing.

[2]  D. Musicki.  Limits of linear multitarget tracking , 2005, 2005 7th International Conference on Information Fusion.

[3]  Oliver E. Drummond,et al.  Performance evaluation methods for multiple-target-tracking algorithms , 1991, Defense, Security, and Sensing.

[4]  Samuel J. Davey,et al.  Performance Assessment of Tracking Systems , 1996, Fourth International Symposium on Signal Processing and Its Applications.

[5]  Ronald P. S. Mahler,et al.  Statistical Multisource-Multitarget Information Fusion , 2007 .

[6]  B. Ristic.  A tool for track-while-scan algorithm evaluation , 1999, 1999 Information, Decision and Control. Data and Information Fusion Symposium, Signal Processing and Communications Symposium and Decision and Control Symposium. Proceedings (Cat. No.99EX251).

[7]  E. Kreyszig.  Introductory Functional Analysis With Applications , 1978 .

[8]  Robin J. Evans,et al.  Integrated probabilistic data association , 1994, IEEE Trans. Autom. Control..

[9]  D. Musicki,et al.  Fast multiple target tracking using particle filters , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[10]  Thia Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software , 2001 .

[11]  Oliver E. Drummond,et al.  Performance metrics for multiple-sensor multiple-target tracking , 2000, SPIE Defense + Commercial Sensing.

[12]  Branko Ristic,et al.  Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .

[13]  Ronald P. S. Mahler,et al.  Multitarget miss distance via optimal assignment , 2004, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.