Estimation By Multiple Views Of Outdoor Terrain Modeled By Stochastic Processes

Francois G. Amblard; David B. Cooper; Bruno Cernuschi-Frias

doi:10.1117/12.937710

27 March 1987 Estimation By Multiple Views Of Outdoor Terrain Modeled By Stochastic Processes

Francois G. Amblard, David B. Cooper, Bruno Cernuschi-Frias

Proceedings Volume 0726, Intelligent Robots and Computer Vision V; (1987) https://doi.org/10.1117/12.937710
Event: Cambridge Symposium_Intelligent Robotics Systems, 1986, Cambridge, MA, United States

Abstract

An approach to 3-D surface estimation is introduced where surfaces are modelled as patches of primitive parameterized surfaces, and these parameters are estimated from images taken by cameras in two or more positions. Appropriate parameterized patches for modelling manufactured objects include planar, cylindrical, spherical and unrestricted quadric patches. Any parameterized function can be used. A complex 3-D object can be described as a collection of such patches. For more irregular surfaces such as outdoor terrain, we use a collection of primitive patches linked together as a stochastic process. More specifically, in this paper we use planar primitive patches, and describe their dependence by Markov Random Fields. We then treat 3-D terrain height estimation as stochastic pro-cess estimation given two or more image data sets. To the extent that the models used are appropriate, this should result in the most accurate surface height estimation, object recognition for objects such as boulders, crevices, mountains, etc, occulded surface height estimation, and other information extraction. A simple geometric explanation is given for the estimation algorithm. This paper is one aspect of a new Bayesian approach to stereo vision as presented in [4,5,6].

Citation Download Citation

Francois G. Amblard, David B. Cooper, and Bruno Cernuschi-Frias "Estimation By Multiple Views Of Outdoor Terrain Modeled By Stochastic Processes", Proc. SPIE 0726, Intelligent Robots and Computer Vision V, (27 March 1987); https://doi.org/10.1117/12.937710

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