E. Malis, E. Marchand. Experiments with robust estimation techniques in real-time robot vision. In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'06, Pages 223-228, Beijing, China, October 2006.
Download Hal paper:
Download paper:
Adobe portable document (pdf) 
Copyright notice:
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder. This page is automatically generated by bib2html v217, © Inria 2002-2015, Projet Lagadic
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
@InProceedings{Malis06a,
Author = {Malis, E. and Marchand, E.},
Title = {Experiments with robust estimation techniques in real-time robot vision},
BookTitle = {IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'06},
Pages = {223--228},
Address = {Beijing, China},
Month = {October},
Year = {2006}
}
Get EndNote Reference (.ref)
|
| Lagadic
| Map
| Team
| Publications
| Demonstrations
|
Irisa - Inria - Copyright 2009 © Lagadic Project |
