DocumentCode :
1294208
Title :
Selective stabilization of images acquired by unmanned ground vehicles
Author :
Yao, Y.S. ; Chellapa, R.
Author_Institution :
Pacific Bell, San Ramon, CA, USA
Volume :
13
Issue :
5
fYear :
1997
fDate :
10/1/1997 12:00:00 AM
Firstpage :
693
Lastpage :
708
Abstract :
This paper studies the problem of selective stabilization of images acquired by a camera mounted on a vehicle navigating a rough terrain. Selective stabilization is defined here as the separation of rotational components into smooth and residual oscillatory rotations. We consider both kinematic and kinetic models suitable for capturing these phenomena and achieve their separation. A scheme for detecting the occurrence and disappearance of smooth rotation is devised, and appropriate dynamic laws are employed to achieve selective stabilization. As a by product of the selective stabilization algorithm, 3-D locations of close feature points are estimated in a stabilized frame of reference, thus providing more useful structural information. Experiments using synthetic images for different scenarios show encouraging results of the proposed approach
Keywords :
Kalman filters; image sequences; mobile robots; motion estimation; nonlinear filters; path planning; recursive estimation; robot dynamics; robot kinematics; robot vision; vehicles; 3D locations; dynamic laws; kinematic models; kinetic models; residual oscillatory rotations; rotational components; rough terrain; selective stabilization; smooth rotations; structural information; synthetic images; unmanned ground vehicles; Cameras; Feedback control; Image generation; Kinematics; Kinetic theory; Land vehicles; Motion detection; Navigation; Road vehicles; Vehicle dynamics;
fLanguage :
English
Journal_Title :
Robotics and Automation, IEEE Transactions on
Publisher :
ieee
ISSN :
1042-296X
Type :
jour
DOI :
10.1109/70.631231
Filename :
631231
Link To Document :
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