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Structure from Visual Motion as a Nonlinear Observation Problem

Soatto, S. and Frezza, R. and Perona, P. (1995) Structure from Visual Motion as a Nonlinear Observation Problem. In: Nonlinear control systems design, 1995 : a postprint volume from the 3rd IFAC Symposium, Tahoe City, California, USA, 25-28 June 1995. Pergamon , Tarrytown, NY, pp. 81-86. ISBN 008042371X. https://resolver.caltech.edu/CaltechAUTHORS:20140730-101724134

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Abstract

Over the last decade, estimating scene structure from visual motion has become a central task of computational vision. As it is well known, the estimation task is nonlinear due to the perspective nature of the measurements. One may ask whether there exists a smart choice of coordinates that simplifies the estimation task. In particular, since "linearity" is a coordinate-dependent notion, one may seek for a particular choice of coordinates such that the problem of estimating structure from motion becomes linear and spectrally assignable. Unfortunately, such a choice of coordinates does not exist, even if we allow for a nonlinear change of output coordinates or an embedding into a higher-dimensional state-space. As a consequence of this result, we study some alternative estimators with nonlinear error dynamics which are proved to converge, and legitimate the use of local linearization-based techniques for estimating structure from known motion and visual information. In most of the cases, however, the true motion undergone by the viewer is unknown. We propose a novel dynamic estimator for scene structure which is independent of the motion of the viewer. The method consists in the identification of an Exterior Differential System with parameters on a sphere.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://www.sciencedirect.com/science/article/pii/B9780080423715500186PublisherArticle
http://dx.doi.org/0.1016/B978-0-08-042371-5.50018-6DOIArticle
ORCID:
AuthorORCID
Perona, P.0000-0002-7583-5809
Additional Information:Copyright © 1995 IFAC. Published by Elsevier Ltd. Research sponsored by NSF NYI Award, NSF ERC in Neuromorphic Systems Engineering at Caltech, ONR grant N00014-93-1-0990. Available online 17 June 2014.
Funders:
Funding AgencyGrant Number
NSFUNSPECIFIED
ONRN00014-93-1-0990
Subject Keywords:Visual structure estimation, structure from motion, identification of exterior differential systems, implicit Extended Kalman Filter
Record Number:CaltechAUTHORS:20140730-101724134
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20140730-101724134
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:47654
Collection:CaltechAUTHORS
Deposited By: Caroline Murphy
Deposited On:31 Jul 2014 22:03
Last Modified:03 Oct 2019 06:55

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