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Modeling and Calibrating the Distrib...
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ProQuest Information and Learning Co.
Modeling and Calibrating the Distributed Camera.
Record Type:
Language materials, manuscript : Monograph/item
Title/Author:
Modeling and Calibrating the Distributed Camera./
Author:
Sweeney, Christopher M.
Description:
1 online resource (151 pages)
Notes:
Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.
Subject:
Computer science. -
Online resource:
click for full text (PQDT)
ISBN:
9781339671758
Modeling and Calibrating the Distributed Camera.
Sweeney, Christopher M.
Modeling and Calibrating the Distributed Camera.
- 1 online resource (151 pages)
Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.
Thesis (Ph.D.)--University of California, Santa Barbara, 2016.
Includes bibliographical references
Structure-from-Motion (SfM) is a powerful tool for computing 3D reconstructions from images of a scene and has wide applications in computer vision, scene recognition, and augmented and virtual reality. Standard SfM pipelines make strict assumptions about the capturing devices in order to simplify the process for estimating camera geometry and 3D structure. Specifically, most methods require monocular cameras with known focal length calibration. When considering large-scale SfM from internet photo collections, EXIF calibrations cannot be used reliably. Further, the requirement of single camera systems limits the scalability of SfM.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781339671758Subjects--Topical Terms:
573171
Computer science.
Index Terms--Genre/Form:
554714
Electronic books.
Modeling and Calibrating the Distributed Camera.
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Modeling and Calibrating the Distributed Camera.
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2016
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1 online resource (151 pages)
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Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.
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Advisers: Tobias Hollerer; Matthew Turk.
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Thesis (Ph.D.)--University of California, Santa Barbara, 2016.
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Includes bibliographical references
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Structure-from-Motion (SfM) is a powerful tool for computing 3D reconstructions from images of a scene and has wide applications in computer vision, scene recognition, and augmented and virtual reality. Standard SfM pipelines make strict assumptions about the capturing devices in order to simplify the process for estimating camera geometry and 3D structure. Specifically, most methods require monocular cameras with known focal length calibration. When considering large-scale SfM from internet photo collections, EXIF calibrations cannot be used reliably. Further, the requirement of single camera systems limits the scalability of SfM.
520
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This thesis proposes to remove these constraints by instead considering the collection of cameras as a distributed camera that encapsulates the image and geometric information of all cameras simultaneously. First, I provide full generalizations to the relative camera pose and absolute camera pose problems. These generalizations are more expressive and extend the traditional single-camera problems to distributed cameras, forming the basis for a novel hierarchical SfM pipeline that exhibits state-of-the-art performance on large-scale datasets. Second, I describe two efficient methods for estimating camera focal lengths for the distributed camera when calibration is not available. Finally, I show how removing these constraints enables a simpler, more scalable SfM pipeline that is capable of handling uncalibrated cameras at scale.
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Ann Arbor, Mich. :
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ProQuest,
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2018
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Mode of access: World Wide Web
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Computer science.
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ProQuest Information and Learning Co.
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University of California, Santa Barbara.
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Computer Science.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10103609
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click for full text (PQDT)
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