Title:
Non-Rigid 2D-3D Pose Estimation and 2D Image Segmentation
Non-Rigid 2D-3D Pose Estimation and 2D Image Segmentation
| dc.contributor.author | Sandhu, Romeil | en_US |
| dc.contributor.author | Dambreville, Samuel | en_US |
| dc.contributor.author | Yezzi, Anthony | en_US |
| dc.contributor.author | Tannenbaum, Allen R. | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
| dc.date.accessioned | 2010-03-12T14:57:39Z | |
| dc.date.available | 2010-03-12T14:57:39Z | |
| dc.date.issued | 2009-06 | |
| dc.description | ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | en_US |
| dc.description | DOI: 10.1109/CVPR.2009.5206842 | en_US |
| dc.description | Presented at the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 20-25 June 2009, Miami, FL. | en_US |
| dc.description.abstract | In this work, we present a non-rigid approach to jointly solve the tasks of 2D-3D pose estimation and 2D image segmentation. In general, most frameworks which couple both pose estimation and segmentation assume that one has the exact knowledge of the 3D object. However, in non-ideal conditions, this assumption may be violated if only a general class to which a given shape belongs to is given (e.g., cars, boats, or planes). Thus, the key contribution in this work is to solve the 2D-3D pose estimation and 2D image segmentation for a general class of objects or deformations for which one may not be able to associate a skeleton model. Moreover, the resulting scheme can be viewed as an extension of the framework presented in, in which we include the knowledge of multiple 3D models rather than assuming the exact knowledge of a single 3D shape prior. We provide experimental results that highlight the algorithm's robustness to noise, clutter, occlusion, and shape recovery on several challenging pose estimation and segmentation scenarios. | en_US |
| dc.identifier.citation | Romeil Sandhu, Samuel Dambreville, Anthony Yezzi, and Allen Tannenbaum, "Non-rigid 2D-3D pose estimation and 2D image segmentation," IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2009, 786-793. | en_US |
| dc.identifier.isbn | 978-1-4244-3992-8 | |
| dc.identifier.issn | 1063-6919 | |
| dc.identifier.uri | http://hdl.handle.net/1853/32150 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | Institute of Electrical and Electronics Engineers | en_US |
| dc.subject | Image segmentation | en_US |
| dc.subject | Image thinning | en_US |
| dc.subject | Pose estimation | en_US |
| dc.title | Non-Rigid 2D-3D Pose Estimation and 2D Image Segmentation | en_US |
| dc.type | Text | |
| dc.type.genre | Proceedings | |
| dspace.entity.type | Publication | |
| local.contributor.author | Yezzi, Anthony | |
| local.contributor.corporatename | School of Electrical and Computer Engineering | |
| local.contributor.corporatename | College of Engineering | |
| local.contributor.corporatename | Wallace H. Coulter Department of Biomedical Engineering | |
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