TY - GEN
T1 - Tracking multiple closely spaced targets using an adaptive foveal sensor
AU - Xi, Fengjun
AU - Morrell, Darryl
PY - 2005/1/1
Y1 - 2005/1/1
N2 - We address the problem of configuring a foveal sensor to track multiple, closely spaced moving targets. The foveal sensor has a high acuity region, whose center and extent can be configured, surrounded by a low acuity region. We study three heuristic approaches to extend a near-optimal greedy configuration rule for a single target to multiple targets: simultaneously observe all targets (SO), center the foveal region on each target in turn (TO), and center the foveal region on the target with the worst position estimate (WO). The target tracker is implemented using a particle filter with joint probabilistic data association (JPDA). Additionally, we implement two different independent-partition proposal distributions using JPDA and global nearest neighbor (GNN). Monte Carlo simulations show that the WO rule outperforms the other rules and that the IP-JPDA proposal gives better tracking performance.
AB - We address the problem of configuring a foveal sensor to track multiple, closely spaced moving targets. The foveal sensor has a high acuity region, whose center and extent can be configured, surrounded by a low acuity region. We study three heuristic approaches to extend a near-optimal greedy configuration rule for a single target to multiple targets: simultaneously observe all targets (SO), center the foveal region on each target in turn (TO), and center the foveal region on the target with the worst position estimate (WO). The target tracker is implemented using a particle filter with joint probabilistic data association (JPDA). Additionally, we implement two different independent-partition proposal distributions using JPDA and global nearest neighbor (GNN). Monte Carlo simulations show that the WO rule outperforms the other rules and that the IP-JPDA proposal gives better tracking performance.
UR - http://www.scopus.com/inward/record.url?scp=33646776428&partnerID=8YFLogxK
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U2 - 10.1109/ICASSP.2005.1416460
DO - 10.1109/ICASSP.2005.1416460
M3 - Conference contribution
AN - SCOPUS:33646776428
SN - 0780388747
SN - 9780780388741
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - V941-V944
BT - 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Y2 - 18 March 2005 through 23 March 2005
ER -