DocumentCode
3419001
Title
Extended feature-based object tracking in presence of data association uncertainty
Author
Alvarez, M.S. ; Regazzoni, C.S.
Author_Institution
Dept. of Biophys. & Electron. Eng., Univ. of Genoa, Genoa, Italy
fYear
2011
fDate
Aug. 30 2011-Sept. 2 2011
Firstpage
136
Lastpage
141
Abstract
This paper proposes and algorithm for extended object tracking using sparse feature points. The described technique is based on the Rao-Blackwellized Particle Filter. In particular, two different data association techniques that take into consideration clutter and missed detections, are coupled and tested in order to provide a comparison of their performance for the problem of extended object tracking.
Keywords
Monte Carlo methods; object tracking; particle filtering (numerical methods); probability; MCDA; Monte Carlo data asociation; PDAF; RBPF; Rao-blackwellized particle filter; data association uncertainty; extended feature-based object tracking; extended visual object tracking; probabilistic data association filter; sparse feature points; Clutter; Equations; Mathematical model; Shape; Target tracking; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Video and Signal-Based Surveillance (AVSS), 2011 8th IEEE International Conference on
Conference_Location
Klagenfurt
Print_ISBN
978-1-4577-0844-2
Electronic_ISBN
978-1-4577-0843-5
Type
conf
DOI
10.1109/AVSS.2011.6027308
Filename
6027308
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