Is covariance information useful in estimating vision parameters?

Michael J. Brooks; Wojciech Chojnacki; Darren Gawley; Anton van den Hengel

doi:10.1117/12.410875

22 December 2000 Is covariance information useful in estimating vision parameters?

Michael J. Brooks, Wojciech Chojnacki, Darren Gawley, Anton van den Hengel

Proceedings Volume 4309, Videometrics and Optical Methods for 3D Shape Measurement; (2000) https://doi.org/10.1117/12.410875
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

This paper assesses some of the practical ramifications of recent developments in estimating vision parameters given information characterizing the uncertainty of the data. This uncertainty information may sometimes be estimated in association with the observation process, and is usually represented in the form of covariance matrices. An empirical study is made of the conditions under which improved parameter estimates can be obtained from data when covariance information is available. We explore, in the case of fundamental matrix estimation and conic fitting, the extent to which the noise should be anisotropic and inhomogeneous if improvements over traditional methods are to be obtained. Critical in this is the devising of synthetic experiments under which noise conditions can be precisely controlled. Given that covariance information is, in itself, subject to estimation error, testes are also undertaken to determine the impact of imprecise covariance information upon the quality of parameter estimates. We thus investigate the consequences for parameter estimation of inaccuracies in the characteristiziaton of noise that inevitably arise in practical computation.

Citation Download Citation

Michael J. Brooks, Wojciech Chojnacki, Darren Gawley, and Anton van den Hengel "Is covariance information useful in estimating vision parameters?", Proc. SPIE 4309, Videometrics and Optical Methods for 3D Shape Measurement, (22 December 2000); https://doi.org/10.1117/12.410875

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available