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Pose estimation of line cameras usin...

Lee, Young-Ran.

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Pose estimation of line cameras using linear features.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Pose estimation of line cameras using linear features./
Author:	Lee, Young-Ran.
Description:	162 p.
Notes:	Advisers: Ayman Habib; Anton F. Schenk.
Contained By:	Dissertation Abstracts International63-04B.
Subject:	Geodesy. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3049066
ISBN:	9780493634661

Pose estimation of line cameras using linear features.
Lee, Young-Ran.

Pose estimation of line cameras using linear features. - 162 p.

Advisers: Ayman Habib; Anton F. Schenk.

Thesis (Ph.D.)--The Ohio State University, 2002.

Pose estimation, which determines positions and orientations of the camera, is a prerequisite for subsequent steps in a mapping project. As digital imagery becomes more popular in photogrammetric applications, features other than points are increasingly employed in pose estimation. For frame imagery, prior research has incorporated geometric constraints into the bundle adjustment to take advantage of high-level features, such as straight lines, which are frequently encountered in the object space. This study introduces high-level feature constraints in the pose estimation problem for aerial line scanners. Since aerial digital scanners have unstable trajectories, the position and orientation should be estimated for every scan line. Generally, it has been believed that robust geometric solutions for a dynamic (non-frame) sensor systems cannot be obtained without the accurate measurements of Global Positioning System (GPS) and Inertial Navigation system (INS), which determine a direct and continuous trajectory of the sensor system. This study attempts to challenge, in part, this argument by showing that the unknown orientation parameters can be solved independently by including linear features in an indirect orientation solution that is less dependent on GPS/INS data. This indirect orientation is achieved by incorporating a straight line constraint in the bundle adjustment for aerial linear array scanners. The mathematical basis of this geometric constraint (co-planarity) is the perspective transformation of straight lines between the image space and object space. A scene captured by an aerial line scanner is composed of sequence of images, each of which may be slightly shifted against each other due to changes in the systems's trajectory. As a result, straight lines in object space do not appear as straight lines in image space. The straight-line constraint is proposed in this study to cope with this problem. This constraint makes use of straight-line features in object space to aid independent recovery of exterior orientation parameters of the entire scan lines as well as to increase geometric strength of the bundle adjustment. Experiments conducted in this study show the effectiveness of using free-form curved features as well as straight-line feature on the recovery for the exterior orientation parameters of aerial line scanners.

ISBN: 9780493634661Subjects--Topical Terms:

550741
Geodesy.

Pose estimation of line cameras using linear features.
LDR:03266nam 2200277 a 45 001 970095
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008 110921s2002 eng d
020 $a 9780493634661
035 $a (UnM)AAI3049066
035 $a AAI3049066
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100 1 $a Lee, Young-Ran. $3 1294144
245 1 0 $a Pose estimation of line cameras using linear features.
300 $a 162 p.
500 $a Advisers: Ayman Habib; Anton F. Schenk.
500 $a Source: Dissertation Abstracts International, Volume: 63-04, Section: B, page: 1752.
502 $a Thesis (Ph.D.)--The Ohio State University, 2002.
520 $a Pose estimation, which determines positions and orientations of the camera, is a prerequisite for subsequent steps in a mapping project. As digital imagery becomes more popular in photogrammetric applications, features other than points are increasingly employed in pose estimation. For frame imagery, prior research has incorporated geometric constraints into the bundle adjustment to take advantage of high-level features, such as straight lines, which are frequently encountered in the object space. This study introduces high-level feature constraints in the pose estimation problem for aerial line scanners. Since aerial digital scanners have unstable trajectories, the position and orientation should be estimated for every scan line. Generally, it has been believed that robust geometric solutions for a dynamic (non-frame) sensor systems cannot be obtained without the accurate measurements of Global Positioning System (GPS) and Inertial Navigation system (INS), which determine a direct and continuous trajectory of the sensor system. This study attempts to challenge, in part, this argument by showing that the unknown orientation parameters can be solved independently by including linear features in an indirect orientation solution that is less dependent on GPS/INS data. This indirect orientation is achieved by incorporating a straight line constraint in the bundle adjustment for aerial linear array scanners. The mathematical basis of this geometric constraint (co-planarity) is the perspective transformation of straight lines between the image space and object space. A scene captured by an aerial line scanner is composed of sequence of images, each of which may be slightly shifted against each other due to changes in the systems's trajectory. As a result, straight lines in object space do not appear as straight lines in image space. The straight-line constraint is proposed in this study to cope with this problem. This constraint makes use of straight-line features in object space to aid independent recovery of exterior orientation parameters of the entire scan lines as well as to increase geometric strength of the bundle adjustment. Experiments conducted in this study show the effectiveness of using free-form curved features as well as straight-line feature on the recovery for the exterior orientation parameters of aerial line scanners.
590 $a School code: 0168.
650 4 $a Geodesy. $3 550741
690 $a 0370
710 2 0 $a The Ohio State University. $3 718944
773 0 $t Dissertation Abstracts International $g 63-04B.
790 $a 0168
790 1 0 $a Habib, Ayman, $e advisor
790 1 0 $a Schenk, Anton F., $e advisor
791 $a Ph.D.
792 $a 2002
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3049066