DocumentCode
3179049
Title
Experiments with robust estimation techniques in real-time robot vision
Author
Malis, Ezio ; Marchand, Eric
Author_Institution
INRIA, Sophia-Antipolis
fYear
2006
fDate
Oct. 2006
Firstpage
223
Lastpage
228
Abstract
The goal of this paper is to present an overview of robust estimation techniques with a special focus on robotic vision applications. In this particular context, constraints due computation time have to be considered in the choice of the estimation algorithm. Among the numerous techniques proposed in the literature to obtained robust estimation we have, not being exhaustive, Hough transform, RANSAC (Random Sample Consensus), the LMedS (Least Median of Squares), the M-estimators, etc. In this overview, we describe these various approaches in the light of a simple example. Finally, we illustrate the use of robust estimation techniques by various examples in real-time robot vision
Keywords
Hough transforms; estimation theory; least mean squares methods; robot vision; Hough transform; least median of squares; random sample consensus; real-time robot vision; robust estimation; Cameras; Convergence; Data mining; Electric breakdown; Intelligent robots; Parameter estimation; Robot vision systems; Robustness; Solid modeling; Time factors;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on
Conference_Location
Beijing
Print_ISBN
1-4244-0259-X
Electronic_ISBN
1-4244-0259-X
Type
conf
DOI
10.1109/IROS.2006.282572
Filename
4058722
Link To Document