Single view object completion

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).

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Thorsen, Justin

Contributors dc:contributor

• Hoiem, Derek W.

• Single view object reconstruction
• Object completion from a depth map
• Partial view matching
• Object deformation

Statement dc:rights

• Copyright 2014 Justin Thorsen

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/72806

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/72806