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Title:Single view object completion
Author(s):Thorsen, Justin
Advisor(s):Hoiem, Derek W.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Single view object reconstruction
Object completion from a depth map
Partial view matching
Object deformation
Abstract:The goal of this paper is to achieve complete reconstruction of a 3d object from a single depth image observation. Much effort has been put on multi-view reconstruction of objects with substantial success, but single view recon- struction is still very limited. Initial methods produce only partial reconstructions by projecting a depth map. State of the art approaches achieve complete reconstruction but either require user interaction or perform successfully on only a handful of simple categories. The method described in this paper is an exemplar based approach to fully au- tomated reconstruction of a large variety of object classes using only a single depth image. The approach has three major components: retrieving a similar object, fitting the matched object to the query point cloud using alignment and symmetries, and reconstructing the mesh using the exemplar as a template. This method is evaluated in three distinct experiments: novel category (query of untrained class), novel model (query of trained class, untrained model), and novel view (query of trained model from a new viewpoint).
Issue Date:2015-01-21
URI:http://hdl.handle.net/2142/72806
Rights Information:Copyright 2014 Justin Thorsen
Date Available in IDEALS:2015-01-21
Date Deposited:2014-12


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