TY - GEN
T1 - Box-particle intensity filter
AU - Schikora, M.
AU - Gning, A.
AU - Mihaylova, L.
AU - Cremers, D.
AU - Koch, W.
AU - Streit, R.
PY - 2012
Y1 - 2012
N2 - This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-iFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables this approach to be used for distributed computing. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes the methods from the field of interval analysis. Our studies suggest that the box-iFilter reaches an accuracy similar to a sequential Monte Carlo (SMC) iFilter but with much less computational costs.
AB - This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-iFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables this approach to be used for distributed computing. A box-particle is a random sample that occupies a small and controllable rectangular region of non-zero volume. Manipulation of boxes utilizes the methods from the field of interval analysis. Our studies suggest that the box-iFilter reaches an accuracy similar to a sequential Monte Carlo (SMC) iFilter but with much less computational costs.
KW - Box particle filters
KW - Intensity filter
KW - Interval measurements
KW - Multi-target tracking
KW - Poisson point processes
UR - http://www.scopus.com/inward/record.url?scp=84864654892&partnerID=8YFLogxK
U2 - 10.1049/cp.2012.0405
DO - 10.1049/cp.2012.0405
M3 - Conference contribution
AN - SCOPUS:84864654892
SN - 9781849196246
T3 - IET Conference Publications
SP - 3
BT - 9th IET Data Fusion and Target Tracking Conference, DF and TT 2012
T2 - 9th IET Data Fusion and Target Tracking Conference: Algorithms and Applications, DF and TT 2012
Y2 - 16 May 2012 through 17 May 2012
ER -