3D model-based pose estimation of rigid objects from a single image for robotics
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2015
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| Online Access: | http://hdl.handle.net/1721.1/99817 |
| _version_ | 1826196905710845952 |
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| author | Davies, Samuel Ingraham, 1980- |
| author2 | Tomás Lozano-Pérez and Leslie Pack Kaelbling. |
| author_facet | Tomás Lozano-Pérez and Leslie Pack Kaelbling. Davies, Samuel Ingraham, 1980- |
| author_sort | Davies, Samuel Ingraham, 1980- |
| collection | MIT |
| description | Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. |
| first_indexed | 2024-09-23T10:39:49Z |
| format | Thesis |
| id | mit-1721.1/99817 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:39:49Z |
| publishDate | 2015 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/998172019-04-11T04:32:03Z 3D model-based pose estimation of rigid objects from a single image for robotics 3 dimensional model-based pose estimation of rigid objects from a single image for robotics Davies, Samuel Ingraham, 1980- Tomás Lozano-Pérez and Leslie Pack Kaelbling. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 167-170). We address the problem of finding the best 3D pose for a known object, supported on a horizontal plane, in a cluttered scene in which the object is not significantly occluded. We assume that we are operating with RGB-D images and some information about the pose of the camera. We also assume that a 3D mesh model of the object is available, along with a small number of labeled images of the object. The problem is motivated by robot systems operating in indoor environments that need to manipulate particular objects and therefore need accurate pose estimates. This contrasts with other vision settings in which there is great variability in the objects but precise localization is not required. Our approach is to find the global best object localization in a full 6D space of rigid poses. There are two key components to our approach: (1) learning a view-based model of the object and (2) detecting the object in an image. An object model consists of edge and depth parts whose positions are piece-wise linear functions of the object pose, learned from synthetic rendered images of the 3D mesh model. We search for objects using branch-and-bound search in the space of the depth image (not directly in the Euclidean world space) in order to facilitate an efficient bounding function computed from lower-dimensional data structures. by Samuel I. Davies. Ph. D. 2015-11-09T19:50:46Z 2015-11-09T19:50:46Z 2015 2015 Thesis http://hdl.handle.net/1721.1/99817 927313989 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 170 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Davies, Samuel Ingraham, 1980- 3D model-based pose estimation of rigid objects from a single image for robotics |
| title | 3D model-based pose estimation of rigid objects from a single image for robotics |
| title_full | 3D model-based pose estimation of rigid objects from a single image for robotics |
| title_fullStr | 3D model-based pose estimation of rigid objects from a single image for robotics |
| title_full_unstemmed | 3D model-based pose estimation of rigid objects from a single image for robotics |
| title_short | 3D model-based pose estimation of rigid objects from a single image for robotics |
| title_sort | 3d model based pose estimation of rigid objects from a single image for robotics |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/99817 |
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