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Estimation of motion parameters of a planar body using binocular camera configuration

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Date Issued:
1991
Summary:
This thesis is concerned with the estimation of motion parameters of planar-object surfaces viewed with a binocular camera configuration. Possible application of this method includes autonomous guidance of a moving platform (AGVS) via imaging, and segmentation of moving objects by the use of the information concerning the motion and the structure. The brightness constraint equation is obtained by assuming the brightness of a moving patch as almost invariant. This equation is solved for single camera case as well as binocular camera case by knowing values of the surface normal or by iteratively determining it using the estimates of motion parameters. For this value of the surface normal, rotational and translational motion components are determined over the entire image using a least squares algorithm. This algorithm is tested for simulated images as well as real images pertaining to a single camera as well as binocular camera situations. (Abstract shortened with permission of author.)
Title: Estimation of motion parameters of a planar body using binocular camera configuration.
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Name(s): Haliyur, Padma.
Florida Atlantic University, Degree grantor
Sudhakar, Raghavan, Thesis advisor
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 1991
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 107 p.
Language(s): English
Summary: This thesis is concerned with the estimation of motion parameters of planar-object surfaces viewed with a binocular camera configuration. Possible application of this method includes autonomous guidance of a moving platform (AGVS) via imaging, and segmentation of moving objects by the use of the information concerning the motion and the structure. The brightness constraint equation is obtained by assuming the brightness of a moving patch as almost invariant. This equation is solved for single camera case as well as binocular camera case by knowing values of the surface normal or by iteratively determining it using the estimates of motion parameters. For this value of the surface normal, rotational and translational motion components are determined over the entire image using a least squares algorithm. This algorithm is tested for simulated images as well as real images pertaining to a single camera as well as binocular camera situations. (Abstract shortened with permission of author.)
Identifier: 14692 (digitool), FADT14692 (IID), fau:11483 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 1991.
Subject(s): Motion
Image processing
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/14692
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.