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Single-View 3D Object Shape Estimation

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dc.contributor.advisorElder, James H.
dc.contributor.authorQian, Yiming
dc.date.accessioned2021-03-08T17:20:51Z
dc.date.available2021-03-08T17:20:51Z
dc.date.copyright2020-11
dc.date.issued2021-03-08
dc.date.updated2021-03-08T17:20:51Z
dc.degree.disciplineComputer Science
dc.degree.levelDoctoral
dc.degree.namePhD - Doctor of Philosophy
dc.description.abstractAn accurate single-view 3D reconstruction algorithm would allow researchers to develop better systems in robotics and VR/AR applications. However, single-view 3D reconstruc- tion is an ill-posed problem and thus solvable only for scenes that satisfy strong regularity conditions. Features such as texture variations, haze, colour, shading, known object size and occlusion can provide information about 3D structures. Further, the built environment has repeated patterns and orthogonal straight lines that contain structured information with strong regularities. In this report, I will introduce the research I have done for my PhD on the single-view reconstruction problem in two parts. Part 1 will detail the three research projects I have completed on single-view 3D reconstruction of the built environment: 1) line segment detection [4], 2) single-view geometry-driven road segmentation [5], and 3) single-view 3D reconstruction of Manhattan buildings [158]. Part 2 will detail the research I have done on reconstructing the 3D shape of more general objects from their bounding contours.
dc.identifier.urihttp://hdl.handle.net/10315/38175
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectArtificial intelligence
dc.subject.keywordsComputer vision
dc.subject.keywords3D reconstruction
dc.subject.keywordsSingle-view
dc.titleSingle-View 3D Object Shape Estimation
dc.typeElectronic Thesis or Dissertation

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