Title
Level-set random hypersurface models for tracking nonconvex extended objects.
Abstract
This paper presents a novel approach to track a nonconvex shape approximation of an extended target based on noisy point measurements. For this purpose, a novel type of random hypersurface model (RHM) called Level-set RHM is introduced that models the interior of a shape with level-sets of an implicit function. Based on the Level-set RHM, a nonlinear measurement equation can be derived that allows...
Year
DOI
Venue
2016
10.1109/TAES.2016.130704
IEEE Transactions on Aerospace and Electronic Systems
Keywords
Field
DocType
Shape,Shape measurement,Noise measurement,Target tracking,Mathematical model,Probabilistic logic,Object tracking
Active contour model,Active shape model,Mathematical optimization,Polygon,Noise measurement,Control theory,Level set,Algorithm,Implicit function,Video tracking,Hypersurface,Mathematics
Journal
Volume
Issue
ISSN
52
6
0018-9251
Citations 
PageRank 
References 
5
0.43
11
Authors
4
Name
Order
Citations
PageRank
Antonio Zea1415.25
Florian Faion2747.95
Marcus Baum328532.99
Uwe D. Hanebeck4944133.52