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Using depth and appearance features for informed robot grasping of highly wrinkled clothes
dc.contributor.author | Ramisa Ayats, Arnau |
dc.contributor.author | Alenyà Ribas, Guillem |
dc.contributor.author | Moreno-Noguer, Francesc |
dc.contributor.author | Torras, Carme |
dc.contributor.other | Institut de Robòtica i Informàtica Industrial |
dc.date.accessioned | 2013-01-14T18:10:40Z |
dc.date.available | 2013-01-14T18:10:40Z |
dc.date.created | 2012 |
dc.date.issued | 2012 |
dc.identifier.citation | Ramisa, A. [et al.]. Using depth and appearance features for informed robot grasping of highly wrinkled clothes. A: IEEE International Conference on Robotics and Automation. "Proceedings of the 2012 IEEE International Conference on Robotics and Automation". St. Paul - Minessota: IEEE, 2012, p. 1703-1708. |
dc.identifier.isbn | CFP12RAA-USB |
dc.identifier.uri | http://hdl.handle.net/2117/17358 |
dc.description.abstract | Detecting grasping points is a key problem in cloth manipulation. Most current approaches follow a multiple regrasp strategy for this purpose, in which clothes are sequentially grasped from different points until one of them yields to a desired configuration. In this paper, by contrast, we circumvent the need for multiple re-graspings by building a robust detector that identifies the grasping points, generally in one single step, even when clothes are highly wrinkled. In order to handle the large variability a deformed cloth may have, we build a Bag of Features based detector that combines appearance and 3D geometry features. An image is scanned using a sliding window with a linear classifier, and the candidate windows are refined using a non-linear SVM and a “grasp goodness” criterion to select the best grasping point. We demonstrate our approach detecting collars in deformed polo shirts, using a Kinect camera. Experimental results show a good performance of the proposed method not only in identifying the same trained textile object part under severe deformations and occlusions, but also the corresponding part in other clothes, exhibiting a degree of generalization. |
dc.format.extent | 6 p. |
dc.language.iso | eng |
dc.publisher | IEEE |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo |
dc.subject.lcsh | Computer vision |
dc.subject.other | Computer vision |
dc.title | Using depth and appearance features for informed robot grasping of highly wrinkled clothes |
dc.type | Conference report |
dc.subject.lemac | Visió per ordinador |
dc.contributor.group | Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents |
dc.contributor.group | Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI |
dc.identifier.doi | 10.1109/ICRA.2012.6225045 |
dc.subject.inspec | Classificació INSPEC::Pattern recognition::Computer vision |
dc.relation.publisherversion | http://dx.doi.org/10.1109/ICRA.2012.6225045 |
dc.rights.access | Open Access |
local.identifier.drac | 10805501 |
dc.description.version | Preprint |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/FP7/269959/EU/Intelligent observation and execution of Actions and manipulations/INTELLACT |
local.citation.author | Ramisa, A.; Alenyà, G.; Moreno-Noguer, F.; Torras, C. |
local.citation.contributor | IEEE International Conference on Robotics and Automation |
local.citation.pubplace | St. Paul - Minessota |
local.citation.publicationName | Proceedings of the 2012 IEEE International Conference on Robotics and Automation |
local.citation.startingPage | 1703 |
local.citation.endingPage | 1708 |