Comments on "Joint detection and estimation of multiple objects from image observations"

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dc.contributor.authorDavey, S.
dc.date.issued2012
dc.description.abstractThe above article [1] introduced an algorithm for multitarget track-before-detect based on a multi-Bernoulli random finite set model (MB-TBD). This new algorithm was compared with the Histogram Probabilistic Multi-Hypothesis Tracker (H-PMHT) on simulated data examples containing multiple targets with non-linear dynamics. The authors reported poor performance from H-PMHT and described several deficiencies of the algorithm. This note highlights unnecessary assumptions made in the assessment of H-PMHT and repeats two of the simulation examples after relaxing them. We demonstrate a substantial improvement in performance compared with the originally published results. The simulation example is also shown to be a relatively high signal to noise problem and good performance is obtained from a conventional detect-then-track algorithm.
dc.description.statementofresponsibilitySamuel J. Davey
dc.identifier.citationIEEE Transactions on Signal Processing, 2012; 60(3):1539-1540
dc.identifier.doi10.1109/TSP.2011.2173679
dc.identifier.issn1053-587X
dc.identifier.issn1941-0476
dc.identifier.urihttp://hdl.handle.net/2440/76129
dc.language.isoen
dc.publisherIEEE-Inst Electrical Electronics Engineers Inc
dc.rights© 2011 British Crown Copyright, © 2011 IEEE
dc.source.urihttps://doi.org/10.1109/tsp.2011.2173679
dc.titleComments on "Joint detection and estimation of multiple objects from image observations"
dc.typeJournal article
pubs.publication-statusPublished

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