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Permanent link (DOI): https://doi.org/10.7939/R3Q359

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Theses and Dissertations

A Cluster based Free Viewpoint Video System using Region-tree based Scene Reconstruction Open Access

Descriptions

Other title
Subject/Keyword
Free viewpoint video, stereo matching, optical flow, camera array
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Lei, Cheng
Supervisor and department
Yee-Hong Yang (Computing Science)
Examining committee member and department
Walter Bischof (Computing Science)
Dil Joseph (Electrical and Computer Engineering)
Janelle Harms (Computing Science)
Kiriakos Neoklis Kutulakos (Computer Science, University of Toronto)
Department
Department of Computing Science
Specialization

Date accepted
2009-09-18T15:31:16Z
Graduation date
2009-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Free viewpoint video (FVV) has been widely speculated as one of the next generation of visual media applications. By taking advantage of camera array based multiple imaging techniques, FVV enables free viewpoint navigation to invoke a sense of “being immersed” for the viewers. This thesis presents a cluster based FVV system which is designed as a specific application using a new proposed framework for general camera array applications. Our FVV system enables centralized workflow management and distributed computation to take advantage of the cluster’s computation power for fast FVV-oriented video processing. For its implementation, effort is mainly focused on the FVV workflow stages of multi-view video acquisition and dense depth based scene reconstruction. Specifically, a new automatic method is proposed for the efficient geometric, photometric and temporal calibrations of a camera array. With this novel integrated calibration method, the use of unsynchronized cameras becomes possible and the multi-view video acquisition is made easy, which greatly facilitate the practical use of a FVV (or camera array based) system. On the other hand, the dense depth based FVV scene reconstruction is addressed as an image discrete labeling problem using a novel coarse-to-fine region-tree based framework. As a general framework, its high ranking evaluations in standard binocular stereo matching and optical flow estimation benchmarking show its effectiveness and versatility. By further extending it for general position multi-view temporal stereo and integrating with inconsistency map/background based progressive optimization, spatial-temporal consistency is enforced in a new and unified way, which greatly helps the final FVV rendering quality. Extensive experimental results show that the new system with its accompanying algorithms can provide high quality rendering results.
Language
English
DOI
doi:10.7939/R3Q359
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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