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Robust camera self-calibration.

Hu, Rong.

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Robust camera self-calibration.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Robust camera self-calibration./
Author:	Hu, Rong.
Description:	80 p.
Notes:	Source: Masters Abstracts International, Volume: 40-01, page: 0190.
Contained By:	Masters Abstracts International40-01.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1404999
ISBN:	049326521X

Robust camera self-calibration.
Hu, Rong.

Robust camera self-calibration. - 80 p.

Source: Masters Abstracts International, Volume: 40-01, page: 0190.

Thesis (M.S.)--University of Nevada, Reno, 2001.

In this thesis, we first discuss the camera self-calibration method based on the correspondence of image points. The solution is found to be very sensitive to image noise; Furthermore, since the camera self-calibration is carried out solely on the basis of image correspondence, outliers due to point mismatches can completely spoil the consequent estimation of the unknown parameters.

ISBN: 049326521XSubjects--Topical Terms:

626642
Computer Science.

Robust camera self-calibration.
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020 $a 049326521X
035 $a (UnM)AAI1404999
035 $a AAI1404999
040 $a UnM $c UnM
100 1 $a Hu, Rong. $3 1675249
245 1 0 $a Robust camera self-calibration.
300 $a 80 p.
500 $a Source: Masters Abstracts International, Volume: 40-01, page: 0190.
500 $a Adviser: Qiang Ji.
502 $a Thesis (M.S.)--University of Nevada, Reno, 2001.
520 $a In this thesis, we first discuss the camera self-calibration method based on the correspondence of image points. The solution is found to be very sensitive to image noise; Furthermore, since the camera self-calibration is carried out solely on the basis of image correspondence, outliers due to point mismatches can completely spoil the consequent estimation of the unknown parameters.
520 $a In view of these problems, our research focuses on improving the robustness with respect to image noise and outliers. To this end, we first introduce a non-linear approach to the camera self-calibration using points. We then apply a robust least-median of squares (LMS) method to handle outliers. Finally, we introduce a new camera self-calibration algorithm using ellipses. Compared to points, ellipses can basically eliminate the point mismatch and image occlusion problems. The performance of these algorithms is validated using the synthetic and real image data.
590 $a School code: 0139.
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Industrial. $3 626639
690 $a 0984
690 $a 0540
690 $a 0546
710 2 0 $a University of Nevada, Reno. $3 626634
773 0 $t Masters Abstracts International $g 40-01.
790 1 0 $a Ji, Qiang, $e advisor
790 $a 0139
791 $a M.S.
792 $a 2001
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1404999