Title
A Probabilistic Observer For Visual Tracking
Abstract
This paper describes an observer for estimation of the rigid pose and shape states associated to an object being tracked in an image sequence. The defined observer utilizes standard estimation strategies for the finite-dimensional rigid pose sub-states, and a novel strategy for the shape substates. In particular, the shape sub-state observer utilizes an implicit probability field, where the 50% probability isocontour defines the object shape. A general purpose second-order model and a corresponding correction scheme are defined for the observer state. The observer is applied to recorded imagery and its performance is examined using objective error metrics.
Year
DOI
Venue
2010
10.1109/ACC.2010.5530871
2010 AMERICAN CONTROL CONFERENCE
Keywords
DocType
ISSN
object recognition,visual tracking,image segmentation,object tracking,second order,pose estimation,state observer,shape,bayesian methods
Conference
0743-1619
Citations 
PageRank 
References 
1
0.35
9
Authors
4
Name
Order
Citations
PageRank
Ibrahima J. Ndiour1213.44
Omar Arif2225.87
Jochen Teizer39011.30
Patricio A Vela436939.12