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A Study On Multi-Target Tracking And Phd Filter
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
2012 (English)In: 2011 3rd International Conference On Computer Technology And Development (ICCTD 2011), Vol 2, New York: American Society of Mechanical Engineers , 2012, 781-786 p.Conference paper, Published paper (Refereed)
Abstract [en]

The probability hypothesis density (PHD) filter as an efficient, practical and robust approach to solve the multi-target tracking problem has been successfully implemented. In this paper, a study on multi-target tracking problem and the PHD filter with "lateral and vertical thinking" is proposed. Firstly we list several difficulties (data association, time-varying number, and inaccessible control signal) for multi-target tracking; and then come up with the particle PHD filter as an alternative, while summarizing the algorithm with clarity and perception; finally simulation and analysis further prove the strengthens of PHD filter.

Place, publisher, year, edition, pages
New York: American Society of Mechanical Engineers , 2012. 781-786 p.
Keyword [en]
Multi-target tracking, Random finite sets, Bayesian filtering, Particle PHD filter
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-104289ISI: 000307481500130ISBN: 978-0-7918-5991-9 (print)OAI: oai:DiVA.org:kth-104289DiVA: diva2:563899
Conference
3rd International Conference on Computer Technology and Development (ICCTD 2011),Chengdu,China, NOV 25-27, 2011
Note

QC 20121031

Available from: 2012-10-31 Created: 2012-10-31 Last updated: 2012-10-31Bibliographically approved

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