Cart (Loading....) | Create Account
Close category search window
 

Performance evaluation of a class of M-estimators for surface parameter estimation in noisy range data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Mirza, M.J. ; Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA ; Boyer, K.L.

Depth maps are frequently analyzed as if the errors are normally, identically, and independently distributed. This noise model does not consider at least two types of anomalies encountered in sampling: a few large deviations in the data (outliers) and a uniformly distributed error component arising from rounding and quantization. The theory of robust statistics, which formally addresses these problems, is used in a robust sequential estimator (RSE) of the authors' design. The RSE assigns different weights to each observation based on maximum-likelihood analysis, assuming that the errors follow a t distribution which represents the outliers more realistically. This concept is extended to several well-known maximum-likelihood estimators (M-estimators). Since most M-estimators do not have a target distribution, the weights are obtained by a simple linearization and then embedded in the same RSE algorithm. Experimental results over a variety of real and synthetic range imagery are presented, and the performance of these estimators is evaluated under different noise conditions

Published in:

Robotics and Automation, IEEE Transactions on  (Volume:9 ,  Issue: 1 )

Date of Publication:

Feb 1993

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.