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Accurate real-time reconstruction of...

Templeton, Todd Russell.

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Accurate real-time reconstruction of distant scenes using computer vision: The recursive Multi-Frame Planar Parallax algorithm.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Accurate real-time reconstruction of distant scenes using computer vision: The recursive Multi-Frame Planar Parallax algorithm./
Author:	Templeton, Todd Russell.
Description:	66 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-11, Section: B, page: 6871.
Contained By:	Dissertation Abstracts International71-11B.
Subject:	Engineering, Robotics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3426585
ISBN:	9781124278001

Accurate real-time reconstruction of distant scenes using computer vision: The recursive Multi-Frame Planar Parallax algorithm.
Templeton, Todd Russell.

Accurate real-time reconstruction of distant scenes using computer vision: The recursive Multi-Frame Planar Parallax algorithm. - 66 p.

Source: Dissertation Abstracts International, Volume: 71-11, Section: B, page: 6871.

Thesis (Ph.D.)--University of California, Berkeley, 2009.

In this dissertation, we detail the Recursive Multi-Frame Planar Parallax (RMFPP) algorithm, a recursive extension of Irani et al.'s Multi-Frame Planar Parallax (MFPP) batch algorithm that allows real-time reconstruction of distant static scenes using computer vision, with expected error that increases only linearly with depth. We present an overview and comprehensive derivation of the theoretical foundation on which the RMFPP algorithm is built, including the seminal planar-parallax work by Sawhney. We derive a recursive cost function that preserves more of the problem's nonlinearity than does the cost function in the MFPP algorithm, which allows a more accurate recursive procedure. In order to obtain a recursive algorithm, we remove the geometry-refining optimization that is present in the MFPP algorithm; however, we empirically show that our algorithm degrades gracefully in the presence of geometric error. We present results using both synthetic and real imagery that show that the RMFPP algorithm is at least as accurate as the original MFPP batch algorithm in many circumstances, is preferred to both fixed- and dynamic-baseline two-frame methods, and is suitable for real-time use.

ISBN: 9781124278001Subjects--Topical Terms:

1018454
Engineering, Robotics.

Accurate real-time reconstruction of distant scenes using computer vision: The recursive Multi-Frame Planar Parallax algorithm.
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020 $a 9781124278001
035 $a (UMI)AAI3426585
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040 $a UMI $c UMI
100 1 $a Templeton, Todd Russell. $3 1678251
245 1 0 $a Accurate real-time reconstruction of distant scenes using computer vision: The recursive Multi-Frame Planar Parallax algorithm.
300 $a 66 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-11, Section: B, page: 6871.
500 $a Adviser: S. Shankar Sastry.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2009.
520 $a In this dissertation, we detail the Recursive Multi-Frame Planar Parallax (RMFPP) algorithm, a recursive extension of Irani et al.'s Multi-Frame Planar Parallax (MFPP) batch algorithm that allows real-time reconstruction of distant static scenes using computer vision, with expected error that increases only linearly with depth. We present an overview and comprehensive derivation of the theoretical foundation on which the RMFPP algorithm is built, including the seminal planar-parallax work by Sawhney. We derive a recursive cost function that preserves more of the problem's nonlinearity than does the cost function in the MFPP algorithm, which allows a more accurate recursive procedure. In order to obtain a recursive algorithm, we remove the geometry-refining optimization that is present in the MFPP algorithm; however, we empirically show that our algorithm degrades gracefully in the presence of geometric error. We present results using both synthetic and real imagery that show that the RMFPP algorithm is at least as accurate as the original MFPP batch algorithm in many circumstances, is preferred to both fixed- and dynamic-baseline two-frame methods, and is suitable for real-time use.
590 $a School code: 0028.
650 4 $a Engineering, Robotics. $3 1018454
650 4 $a Artificial Intelligence. $3 769149
690 $a 0771
690 $a 0800
710 2 $a University of California, Berkeley. $b Electrical Engineering & Computer Sciences. $3 1671057
773 0 $t Dissertation Abstracts International $g 71-11B.
790 1 0 $a Sastry, S. Shankar, $e advisor
790 1 0 $a Bajcsy, Ruzena $e committee member
790 1 0 $a Banks, Martin $e committee member
790 $a 0028
791 $a Ph.D.
792 $a 2009
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3426585