TY - GEN
T1 - Tracking efficiency measurement of dynamic models on geometric particle filter using KLD-resampling
AU - Gunawan, Alexander A.S.
AU - Jatmiko, Wisnu
AU - Dewanto, Vektor
AU - Rachmadi, F.
AU - Jovan, F.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/3/23
Y1 - 2014/3/23
N2 - Particle filter has appeared as a useful tool for visual object tracking. The efficiency of the particle filter depends mostly on the number of particles used in the estimation. This paper would like to measure the efficiency of particle filter via the Kullback-Leibler distance (KLD). The basis of the method is similar to Fox's KLD-sampling but implemented differently using resampling. The benefit of this approach is that the underlying distribution is exactly the posterior distribution. By means of batch KLD-resampling, we measure the efficiency of several dynamic models by calculating the average number of needed samples. Using experiments, we found (i) the efficiency of particle filter can be measure reliably enough using batch KLD-resampling, (ii) dynamics models affect the efficiency of particle filter, but their performance depends mostly on the case by case situationally.
AB - Particle filter has appeared as a useful tool for visual object tracking. The efficiency of the particle filter depends mostly on the number of particles used in the estimation. This paper would like to measure the efficiency of particle filter via the Kullback-Leibler distance (KLD). The basis of the method is similar to Fox's KLD-sampling but implemented differently using resampling. The benefit of this approach is that the underlying distribution is exactly the posterior distribution. By means of batch KLD-resampling, we measure the efficiency of several dynamic models by calculating the average number of needed samples. Using experiments, we found (i) the efficiency of particle filter can be measure reliably enough using batch KLD-resampling, (ii) dynamics models affect the efficiency of particle filter, but their performance depends mostly on the case by case situationally.
UR - http://www.scopus.com/inward/record.url?scp=84946690501&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS.2014.7065857
DO - 10.1109/ICACSIS.2014.7065857
M3 - Conference contribution
AN - SCOPUS:84946690501
T3 - Proceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems
SP - 385
EP - 388
BT - Proceedings - ICACSIS 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014
Y2 - 18 October 2014 through 19 October 2014
ER -