Title:
Detecting Partially Occluded Objects via Segmentation and Validation
Detecting Partially Occluded Objects via Segmentation and Validation
| dc.contributor.author | Levihn, Martin | |
| dc.contributor.author | Dutton, Matthew | |
| dc.contributor.author | Trevor, Alexander J. B. | |
| dc.contributor.author | Stilman, Mike | |
| dc.contributor.corporatename | Georgia Institute of Technology. Center for Robotics and Intelligent Machines | en_US |
| dc.date.accessioned | 2013-07-18T15:55:36Z | |
| dc.date.available | 2013-07-18T15:55:36Z | |
| dc.date.issued | 2013-01 | |
| dc.description | © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
| dc.description | Presented at the 2013 IEEE Workshop on Robot Vision (WORV 2013), 15-17 January 2013, Clearwater, FL. | |
| dc.description | DOI: 10.1109/WORV.2013.6521925 | |
| dc.description.abstract | This paper presents a novel algorithm: Verfied Partial Object Detector (VPOD) for accurate detection of partially occluded objects such as furniture in 3D point clouds. VPOD is implemented and validated on real sensor data obtained by our robot. It extends Viewpoint Feature His- tograms (VFH), which classify unoccluded objects, to also classify partially occluded objects such as furniture that might be seen in typical office environments. To achieve this result, VPOD employs two strategies. First, object models are segmented and the object database is extended to include partial models. Second, once a matching partial object is detected, the complete object model is aligned back into the scene and verified for consistency with the point cloud data. Overall, our approach increases the number of objects found and substantially reduces false positives due to the verification process. | en_US |
| dc.embargo.terms | null | en_US |
| dc.identifier.citation | Levihn, M.; Dutton, M.; Trevor, A.J.B.; Stilman, M. (2013). "Detecting Partially Occluded Objects via Segmentation and Validation". Proceedings of the IEEE Workshop on Robot Vision (WORV 2013), 15-17 January 2013, pp.7-13. | en_US |
| dc.identifier.doi | 10.1109/WORV.2013.6521925 | |
| dc.identifier.isbn | 978-1-4673-5646-6 | |
| dc.identifier.uri | http://hdl.handle.net/1853/48451 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | Institute of Electrical and Electronics Engineers | |
| dc.subject | Object detection | en_US |
| dc.subject | Point clouds | en_US |
| dc.subject | Robots | en_US |
| dc.subject | Segmentation | en_US |
| dc.subject | Validation | en_US |
| dc.subject | Verfied partial object detector | en_US |
| dc.subject | Viewpoint feature histograms | en_US |
| dc.title | Detecting Partially Occluded Objects via Segmentation and Validation | en_US |
| dc.type | Text | |
| dc.type.genre | Post-print | |
| dc.type.genre | Proceedings | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | Humanoid Robotics Laboratory | |
| relation.isOrgUnitOfPublication | 05bf85fb-965e-425d-af8b-dbf56e0d9797 |